diff --git a/.gitignore b/.gitignore
index 526ab120f..a505dbc3e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,4 @@
-cmake-build-debug
+cmake-build-*
 build
 Build
 *.*~
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 000000000..e69633365
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,33 @@
+FROM osrf/ros:noetic-desktop-full
+
+# =========================================================
+# =========================================================
+
+# Are you are looking for how to use this docker file?
+#   - https://docs.openvins.com/dev-docker.html
+#   - https://docs.docker.com/get-started/
+#   - http://wiki.ros.org/docker/Tutorials/Docker
+
+# =========================================================
+# =========================================================
+
+# Dependencies we use, catkin tools is very good build system
+# Also some helper utitiles for fast in terminal edits (nano etc)
+RUN apt-get update && apt-get install -y libeigen3-dev nano git cmake
+RUN sudo apt-get install -y python3-catkin-tools python3-osrf-pycommon
+
+# Install deps needed for clion remote debugging
+# https://blog.jetbrains.com/clion/2020/01/using-docker-with-clion/
+RUN apt-get update && apt-get install -y ssh build-essential gcc g++ \
+    gdb clang cmake rsync tar python && apt-get clean
+RUN ( \
+    echo 'LogLevel DEBUG2'; \
+    echo 'PermitRootLogin yes'; \
+    echo 'PasswordAuthentication yes'; \
+    echo 'Subsystem sftp /usr/lib/openssh/sftp-server'; \
+  ) > /etc/ssh/sshd_config_test_clion \
+  && mkdir /run/sshd
+RUN useradd -m user && yes password | passwd user
+RUN usermod -s /bin/bash user
+CMD ["/usr/sbin/sshd", "-D", "-e", "-f", "/etc/ssh/sshd_config_test_clion"]
+
diff --git a/ReadMe.md b/ReadMe.md
index 65e8fceb1..ee8f5e956 100644
--- a/ReadMe.md
+++ b/ReadMe.md
@@ -18,6 +18,7 @@ Please take a look at the feature list below for full details on what the system
 
 ## News / Events
 
+* **July 19, 2021** - Camera classes, masking support, alignment utility, and other small fixes. See v2.4 [PR#117](https://github.com/rpng/open_vins/pull/186) for details.
 * **December 1, 2020** - Released improved memory management, active feature pointcloud publishing, limiting number of features in update to bound compute, and other small fixes. See v2.3 [PR#117](https://github.com/rpng/open_vins/pull/117) for details.
 * **November 18, 2020** - Released groundtruth generation utility package, [vicon2gt](https://github.com/rpng/vicon2gt) to enable creation of groundtruth trajectories in a motion capture room for evaulating VIO methods.
 * **July 7, 2020** - Released zero velocity update for vehicle applications and direct initialization when standing still. See [PR#79](https://github.com/rpng/open_vins/pull/79) for details. 
@@ -62,9 +63,10 @@ Please take a look at the feature list below for full details on what the system
     * Stereo camera
     * Binocular camera
     * KLT or descriptor based
+    * Masked tracking
 * Static IMU initialization (sfm will be open sourced later)
 * Zero velocity detection and updates
-* Out of the box evaluation on EurocMav and TUM-VI datasets
+* Out of the box evaluation on EurocMav, TUM-VI, UZH-FPV, KAIST Urban and VIO datasets
 * Extensive evaluation suite (ATE, RPE, NEES, RMSE, etc..)
 
 
diff --git a/docs/bib/extra.bib b/docs/bib/extra.bib
index 121d92590..783aa7566 100644
--- a/docs/bib/extra.bib
+++ b/docs/bib/extra.bib
@@ -216,3 +216,16 @@ @inproceedings{Davidson2009ENC
     year={2009},
     url = {http://www.tkt.cs.tut.fi/research/nappo_files/1_C2.pdf},
 }
+
+@article{Jeon2021RAL,
+    title={Run your visual-inertial odometry on NVIDIA Jetson: Benchmark tests on a micro aerial vehicle},
+    author={Jeon, Jinwoo and Jung, Sungwook and Lee, Eungchang and Choi, Duckyu and Myung, Hyun},
+    journal={IEEE Robotics and Automation Letters},
+    volume={6},
+    number={3},
+    pages={5332--5339},
+    year={2021},
+    publisher={IEEE}
+}
+
+
diff --git a/docs/dev-docker.dox b/docs/dev-docker.dox
new file mode 100644
index 000000000..33d50b437
--- /dev/null
+++ b/docs/dev-docker.dox
@@ -0,0 +1,194 @@
+/**
+
+
+@page dev-docker Developing with Docker
+@tableofcontents
+
+
+@section dev-docker-install Installing Docker
+
+This will differ on which operating system you have installed, this guide is for linux-based systems.
+Please take a look at the official Docker [Get Docker](https://docs.docker.com/get-docker/) guide.
+There is also a guide from ROS called [getting started with ROS and Docker](http://wiki.ros.org/docker/Tutorials/Docker).
+On Ubuntu one should be able to do the following to get docker:
+
+@code{.shell-session}
+curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg
+echo "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
+sudo apt-get update
+sudo apt-get install docker-ce docker-ce-cli containerd.io
+@endcode
+
+From there we can install [NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-docker) to allow for the docker to use our GPU and for easy GUI pass through.
+You might also want to check out [this](https://roboticseabass.wordpress.com/2021/04/21/docker-and-ros/) blogpost for some more details.
+
+@code{.shell-session}
+distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
+   && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \
+   && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
+sudo apt-get update
+sudo apt-get install -y nvidia-docker2
+sudo systemctl restart docker
+sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi #to verify install
+@endcode
+
+From this point we should be able to "test" that everything is working ok.
+First on the host machine we need to allow for x11 windows to connect.
+
+@code{.shell-session}
+xhost +
+@endcode
+
+We can now run the following command which should open gazebo GUI on your main desktop window.
+
+@code{.shell-session}
+docker run -it --net=host --gpus all \
+    --env="NVIDIA_DRIVER_CAPABILITIES=all" \
+    --env="DISPLAY" \
+    --env="QT_X11_NO_MITSHM=1" \
+    --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
+    osrf/ros:noetic-desktop-full \
+    bash -it -c "roslaunch gazebo_ros empty_world.launch"
+@endcode
+
+Alternatively we can launch directly into a bash shell and run commands from in there.
+This basically gives you a terminal in the docker container.
+
+@code{.shell-session}
+docker run -it --net=host --gpus all \
+    --env="NVIDIA_DRIVER_CAPABILITIES=all" \
+    --env="DISPLAY" \
+    --env="QT_X11_NO_MITSHM=1" \
+    --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
+    osrf/ros:noetic-desktop-full \
+    bash
+# you should be able to launch rviz once in bash
+rviz
+@endcode
+
+
+@section dev-docker-openvins Running OpenVINS with Docker
+
+Clone the OpenVINS repository, build the container and then launch it.
+The [Dockerfile](https://github.com/rpng/open_vins/blob/master/Dockerfile) will not build the repo by default, thus you will need to build the project.
+
+
+@m_class{m-block m-warning}
+
+@par Use a Workspace Directory Mount
+    Here it is important to note that we are going to create a dedicated ROS *workspace* which will then be loaded into the workspace.
+    Thus if you are going to develop packages alongside OpenVINS you would make sure you have cloned your source code into the same workspace.
+    The workspace local folder will be mounted to `/catkin_ws/` in the docker, thus all changes from the host are mirrored.
+
+@code{.shell-session}
+mkdir -p ~/workspace/catkin_ws_ov/src
+cd ~/workspace/catkin_ws_ov/src
+git clone https://github.com/rpng/open_vins.git
+cd open_vins
+docker build -t openvins .
+cd ~/workspace/catkin_ws_ov
+@endcode
+
+If the dockerfile breaks, you can remove the image and reinstall using the above
+
+@code{.shell-session}
+docker image list
+docker image rm openvins --force
+@endcode
+
+From here it is a good idea to create a nice helper command which will launch the docker and also pass the GUI to your host machine.
+Here you can append it to the bottom of the ~/.bashrc so that we always have it on startup or just run the two commands on each restart
+
+@m_class{m-block m-warning}
+
+@par Directory Binding
+    You will need to specify *absolute directory paths* to the workspace and dataset folders on the host you want to bind.
+    Bind mounts are used to ensure that the host directory is directly used and all edits made on the host are sync'ed with
+    the docker container. See the docker [bind mounts](https://docs.docker.com/storage/bind-mounts/) documentation. You
+    can add and remove mounts from this command as you see the need.
+
+@code{.shell-session}
+nano ~/.bashrc
+# add to the bashrc file
+xhost + &> /dev/null
+export DOCKER_CATKINWS=/home/username/workspace/catkin_ws_ov
+export DOCKER_DATASETS=/home/username/datasets
+alias ov_docker="docker run -it --net=host --gpus all \
+    --env=\"NVIDIA_DRIVER_CAPABILITIES=all\" --env=\"DISPLAY\" \
+    --env=\"QT_X11_NO_MITSHM=1\" --volume=\"/tmp/.X11-unix:/tmp/.X11-unix:rw\" \
+    --mount type=bind,source=$DOCKER_CATKINWS,target=/catkin_ws \
+    --mount type=bind,source=$DOCKER_DATASETS,target=/datasets \
+    openvins $1"
+# save and exit
+source ~/.bashrc
+@endcode
+
+Now we can launch RVIZ and also compile the OpenVINS codebase.
+From two different terminals on the host machine one can run the following:
+
+@code{.shell-session}
+ov_docker roscore
+ov_docker rosrun rviz rviz -d /catkin_ws/src/open_vins/ov_msckf/launch/display.rviz
+ov_docker bash
+@endcode
+
+Now once inside the docker with the bash shell we can build and launch an example simulation:
+
+@code{.shell-session}
+cd catkin_ws
+catkin build
+source devel/setup.bash
+roslaunch ov_msckf pgeneva_sim.launch
+@endcode
+
+@m_class{m-block m-danger}
+
+@par Real-time Performance
+    On my machine running inside of the docker container is not real-time in nature. I am not sure why this is the case
+    if someone knows if something is setup incorrectly please open a github issue. Thus it is recommended to only use
+    the "serial" nodes which allows for the same parameters to be used as when installing directly on an OS.
+
+
+@section dev-docker-clion Using Jetbrains Clion and Docker
+
+Jetbrains provides some instructions on their side and a youtube video.
+Basically, Clion needs to be configured to use an external compile service and this service
+needs to be exposed from the docker container.
+I still recommend users compile with `catkin build` directly in the docker, but this will allow for debugging and syntax insights.
+
+- https://blog.jetbrains.com/clion/2020/01/using-docker-with-clion/
+- https://www.youtube.com/watch?v=h69XLiMtCT8
+
+After building the OpenVINS image (as above) we can do the following which will start a detached process in the docker.
+This process will allow us to connect Clion to it.
+
+@code{.shell-session}
+docker run -d --cap-add sys_ptrace -p127.0.0.1:2222:22 --name clion_remote_env openvins
+@endcode
+
+We can now change Clion to use the docker remote:
+
+1. In short, you should add a new Toolchain entry in settings under Build, Execution, Deployment as a Remote Host type.
+2. Click in the Credentials section and fill out the SSH credentials we set-up in the Dockerfile
+    - Host: localhost
+    - Port: 2222
+    - Username: user
+    - Password: password
+3. Add a CMake profile that uses this toolchain and you’re done.
+4. Change build target to be this new CMake profile (optionally just edit / delete the default)
+
+To add support for ROS you will need to manually set environmental variables in the CMake profile.
+These were generated by going into the ROS workspace, building a package, and then looking at `printenv` output.
+It should be under `Settings > Build,Execution,Deployment > CMake > (your profile) > Environment`.
+This might be a brittle method, but not sure what else to do... (also see [this](https://www.allaban.me/posts/2020/08/ros2-setup-ide-docker/) blog post).
+
+@code{.shell-session}
+LD_PATH_LIB=/catkin_ws/devel/lib:/opt/ros/noetic/lib;PYTHON_EXECUTABLE=/usr/bin/python3;PYTHON_INCLUDE_DIR=/usr/include/python3.8;ROS_VERSION=1;CMAKE_PREFIX_PATH=/catkin_ws/devel:/opt/ros/noetic;LD_LIBRARY_PATH=/catkin_ws/devel/lib:/opt/ros/noetic/lib;PATH=/opt/ros/noetic/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin;PKG_CONFIG_PATH=/catkin_ws/devel/lib/pkgconfig:/opt/ros/noetic/lib/pkgconfig;PYTHONPATH=/opt/ros/noetic/lib/python3/dist-packages;ROSLISP_PACKAGE_DIRECTORIES=/catkin_ws/devel/share/common-lisp;ROS_PACKAGE_PATH=/catkin_ws/src/open_vins/ov_core:/catkin_ws/src/open_vins/ov_data:/catkin_ws/src/open_vins/ov_eval:/catkin_ws/src/open_vins/ov_msckf:/opt/ros/noetic/share
+@endcode
+
+When you build in Clion you should see in `docker stats` that the `clion_remote_env` is building the files and maxing out the CPU during this process.
+Clion should send the source files to the remote server and then on build should build and run it remotely within the docker container.
+A user might also want to edit `Build,Execution,Deployment > Deployment` settings to exclude certain folders from copying over.
+See this [jetbrains documentation page](https://www.jetbrains.com/help/clion/remote-projects-support.html) for more details.
+
+*/
\ No newline at end of file
diff --git a/docs/dev-welcome.dox b/docs/dev-welcome.dox
index f5b6995c6..cc9bc2fa3 100644
--- a/docs/dev-welcome.dox
+++ b/docs/dev-welcome.dox
@@ -4,11 +4,11 @@
 @page dev-welcome Internals and Developers
 
 -   @subpage dev-coding-style --- General coding styles and conventions
+-   @subpage dev-docker --- How to use docker images to develop with
 -   @subpage dev-docs --- Developer guide on how documentation can be built
 -   @subpage dev-index --- Description of the covariance index system
 -   @subpage dev-roadmap --- Where we plan to go in the future
 -   @subpage dev-profiling --- Some notes on performing profiling
 
 
-
 */
\ No newline at end of file
diff --git a/docs/gs-datasets.dox b/docs/gs-datasets.dox
index e3ab4a278..951d21586 100644
--- a/docs/gs-datasets.dox
+++ b/docs/gs-datasets.dox
@@ -157,6 +157,15 @@ The dataset was collected in Korea with a vehicle equipped with stereo camera pa
 The camera is 10 Hz, while the Xsens IMU is 100 Hz sensing rate.
 A groundtruth "baseline" trajectory is also provided which is the resulting output from fusion of the FoG, RKT GPS, and wheel encoders.
 
+@m_class{m-block m-warning}
+
+@par Dynamic Environments
+    A challenging open research question is being able to handle dynamic objects seen from the cameras.
+    By default we rely on our tracking 8 point RANSAC to handle these dynamics objects.
+    In the most of the KAIST datasets the majority of the scene can be taken up by other moving vehicles, thus the performance can suffer.
+    Please be aware of this fact.
+
+
 @code{.shell-session}
 git clone https://github.com/rpng/file_player.git
 git clone https://github.com/irapkaist/irp_sen_msgs.git
@@ -166,18 +175,8 @@ rosrun file_player file_player
 
 To use the dataset, the dataset's file player can be used to publish the sensor information on to ROS.
 See the above commands on what packages you need to clone into your ROS workspace.
-One can record a rosbag after manually and use the serial OpenVINS processing node, or use the live node and manually playback the datasets.
 It is important to *disable* the "skip stop section" to ensure that we have continuous sensor feeds.
-Typically we process the datasets at 2x rate so we get a 20 Hz image feed and the datasets can be processed in a more efficient manor.
-
-@m_class{m-block m-warning}
-
-@par Dynamic Environments
-    A challenging open research question is being able to handle dynamic objects seen from the cameras.
-    By default we rely on our tracking 8 point RANSAC to handle these dynamics objects.
-    In the most of the KAIST datasets the majority of the scene can be taken up by other moving vehicles, thus the performance can suffer.
-    Please be aware of this fact.
-    
+Typically we process the datasets at 1.5x rate so we get a ~20 Hz image feed and the datasets can be processed in a more efficient manor.
 
 @m_div{m-text-center}
 | Dataset Name | Length (km) | Dataset Link | Groundtruth Traj. | Example Launch |
@@ -188,6 +187,32 @@ Typically we process the datasets at 2x rate so we get a 20 Hz image feed and th
 @m_enddiv
 
 
+@section gs-data-kaist-vio KAIST VIO Dataset
+
+The [KAIST VIO dataset](https://github.com/zinuok/kaistviodataset) @cite Jeon2021RAL is a dataset of a MAV in an indoor 3.15 x 3.60 x 2.50 meter environment which undergoes various trajectory motions.
+The camera is intel realsense D435i 25 Hz, while the IMU is 100 Hz sensing rate from the pixelhawk 4 unit.
+A groundtruth "baseline" trajectory is also provided from a OptiTrack Mocap system at 50 Hz, the bag files have the marker body frame to IMU frame already applied.
+This topic has been provided in ov_data for convinces sake.
+
+@m_div{m-text-center}
+| Dataset Name | Length (km) | Dataset Link | Groundtruth Traj. | Example Launch |
+|-------------:|--------|--------------|------------------|------------------|
+| circle | 29.99 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/circle/circle.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| circle_fast | 64.15 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/circle/circle_fast.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| circle_head | 35.05 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/circle/circle_head.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| infinite | 29.35 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/infinite/infinite.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| infinite_fast | 54.24 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/infinite/infinite_fast.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| infinite_head | 37.45 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/infinite/infinite_head.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| rotation | 7.82 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/rotation/rotation.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| rotation_fast | 14.55 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/rotation/rotation_fast.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| square | 41.94 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/square/square.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| square_fast | 44.07 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/square/square_fast.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+| square_head | 50.00 | [download](https://urserver.kaist.ac.kr/publicdata/KAIST_VIO_Dataset/square/square_head.bag) | [link](https://github.com/rpng/open_vins/tree/master/ov_data/kaist_vio) | [launch](https://github.com/rpng/open_vins/blob/master/ov_msckf/launch/pgeneva_ros_kaistvio.launch) |
+@m_enddiv
+
+
+
+
 
 
 
diff --git a/docs/gs-installing.dox b/docs/gs-installing.dox
index 1c34b8641..7fe56c797 100644
--- a/docs/gs-installing.dox
+++ b/docs/gs-installing.dox
@@ -13,9 +13,9 @@ See the [opencv_contrib](https://github.com/opencv/opencv_contrib) readme on how
 We have tested building with OpenCV 3.2, 3.3, 3.4, 4.2, and 4.5.
 Please see the official instructions to install ROS:
 
-* [Ubuntu 16.04 ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu) (uses OpenCV 3.3)
-* [Ubuntu 18.04 ROS Melodic](http://wiki.ros.org/melodic/Installation/Ubuntu) (uses OpenCV 3.2)
-* [Ubuntu 20.04 ROS Noetic](http://wiki.ros.org/noetic/Installation/Ubuntu) (uses OpenCV 4.2)
+- [Ubuntu 16.04 ROS Kinetic](http://wiki.ros.org/kinetic/Installation/Ubuntu) (uses OpenCV 3.3)
+- [Ubuntu 18.04 ROS Melodic](http://wiki.ros.org/melodic/Installation/Ubuntu) (uses OpenCV 3.2)
+- [Ubuntu 20.04 ROS Noetic](http://wiki.ros.org/noetic/Installation/Ubuntu) (uses OpenCV 4.2)
 
 
 @m_class{m-block m-warning}
@@ -23,14 +23,14 @@ Please see the official instructions to install ROS:
 @par ROS Usage in OpenVINS
     We do support ROS-free builds, but don't recommend using this interface as we have limited support for it.
     You will need to ensure you have installed OpenCV and Eigen3 which are the only dependencies.
-    If ROS is not found on the system, one can use command line options to run the simulation without any visualization.
+    If ROS is not found on the system, one can use command line options to run the simulation without any visualization or `cmake -DENABLE_CATKIN_ROS=OFF ..`.
     If you are using the ROS-free interface, you will need to properly construct the @ref ov_msckf::VioManagerOptions struct with proper information and feed inertial and image data into the correct functions.
 
 @code{.shell-session}
 sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
 sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
 sudo apt-get update
-export ROS_DISTRO=melodic # kinetic=16.04, melodic=18.04, noetic=20.04
+export ROS_DISTRO=noetic # kinetic=16.04, melodic=18.04, noetic=20.04
 sudo apt-get install ros-$ROS_DISTRO-desktop-full
 echo "source /opt/ros/$ROS_DISTRO/setup.bash" >> ~/.bashrc
 source ~/.bashrc
@@ -55,6 +55,9 @@ make -j8
 sudo make install
 @endcode
 
+If you do not want to build the modules, you should also be able to do this (while it is not as well tested).
+The ArucoTag tracker depends on a non-free module in the contrib repository, thus this will need to be disabled.
+You can disable this with `catkin build -DENABLE_ARUCO_TAGS=OFF` or `cmake -DENABLE_ARUCO_TAGS=OFF ..` in your build folder.
 
 
 @section gs-install-openvins Cloning the OpenVINS Project
diff --git a/ov_core/CMakeLists.txt b/ov_core/CMakeLists.txt
index 3440827e1..7fa4e6735 100644
--- a/ov_core/CMakeLists.txt
+++ b/ov_core/CMakeLists.txt
@@ -14,13 +14,22 @@ if (NOT OpenCV_FOUND)
 endif()
 find_package(Boost REQUIRED COMPONENTS system filesystem thread date_time)
 
-# display message to user
-#message(WARNING "EIGEN VERSION: " ${EIGEN3_VERSION})
+# Display message to user
 message(WARNING "OPENCV VERSION: " ${OpenCV_VERSION})
 message(WARNING "BOOST VERSION: " ${Boost_VERSION})
 
+# If we will compile with aruco support
+option(ENABLE_ARUCO_TAGS "Enable or disable aruco tag (disable if no contrib modules)" ON)
+if (NOT ENABLE_ARUCO_TAGS)
+    add_definitions(-DENABLE_ARUCO_TAGS=0)
+    message(WARNING "DISABLING ARUCOTAG TRACKING!")
+else()
+    add_definitions(-DENABLE_ARUCO_TAGS=1)
+endif()
+
 # Describe catkin project
-if (catkin_FOUND)
+option(ENABLE_CATKIN_ROS "Enable or disable building with ROS (if it is found)" ON)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     add_definitions(-DROS_AVAILABLE=1)
     catkin_package(
             CATKIN_DEPENDS roscpp rosbag tf std_msgs geometry_msgs sensor_msgs nav_msgs visualization_msgs cv_bridge
@@ -28,7 +37,8 @@ if (catkin_FOUND)
             LIBRARIES ov_core_lib
     )
 else()
-    message(WARNING "CATKIN NOT FOUND BUILDING WITHOUT ROS!")
+    add_definitions(-DROS_AVAILABLE=0)
+    message(WARNING "BUILDING WITHOUT ROS!")
 endif()
 
 
@@ -89,12 +99,11 @@ target_include_directories(ov_core_lib PUBLIC src)
 ##################################################
 # Make binary files!
 ##################################################
-if (catkin_FOUND)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     add_executable(test_tracking src/test_tracking.cpp)
     target_link_libraries(test_tracking ov_core_lib ${thirdparty_libraries})
 endif()
 
-
 add_executable(test_webcam src/test_webcam.cpp)
 target_link_libraries(test_webcam ov_core_lib ${thirdparty_libraries})
 
diff --git a/ov_core/src/cam/CamBase.h b/ov_core/src/cam/CamBase.h
new file mode 100644
index 000000000..4b50d0467
--- /dev/null
+++ b/ov_core/src/cam/CamBase.h
@@ -0,0 +1,179 @@
+/*
+ * OpenVINS: An Open Platform for Visual-Inertial Research
+ * Copyright (C) 2021 Patrick Geneva
+ * Copyright (C) 2021 Guoquan Huang
+ * Copyright (C) 2021 OpenVINS Contributors
+ * Copyright (C) 2019 Kevin Eckenhoff
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <https://www.gnu.org/licenses/>.
+ */
+
+#ifndef OV_CORE_CAM_BASE_H
+#define OV_CORE_CAM_BASE_H
+
+#include <Eigen/Eigen>
+#include <unordered_map>
+
+#include <opencv2/opencv.hpp>
+
+namespace ov_core {
+
+/**
+ * @brief Base pinhole camera model class
+ *
+ * This is the base class for all our camera models.
+ * All these models are pinhole cameras, thus just have standard reprojection logic.
+ *
+ * See each base class for detailed examples on each model:
+ *  - @ref ov_core::CamEqui
+ *  - @ref ov_core::CamRadtan
+ */
+class CamBase {
+
+public:
+  /**
+   * @brief This will set and update the camera calibration values.
+   * This should be called on startup for each camera and after update!
+   * @param calib Camera calibration information (f_x & f_y & c_x & c_y & k_1 & k_2 & k_3 & k_4)
+   */
+  virtual void set_value(const Eigen::MatrixXd &calib) {
+
+    // Assert we are of size eight
+    assert(calib.rows() == 8);
+    camera_values = calib;
+
+    // Camera matrix
+    cv::Matx33d tempK;
+    tempK(0, 0) = calib(0);
+    tempK(0, 1) = 0;
+    tempK(0, 2) = calib(2);
+    tempK(1, 0) = 0;
+    tempK(1, 1) = calib(1);
+    tempK(1, 2) = calib(3);
+    tempK(2, 0) = 0;
+    tempK(2, 1) = 0;
+    tempK(2, 2) = 1;
+    camera_k_OPENCV = tempK;
+
+    // Distortion parameters
+    cv::Vec4d tempD;
+    tempD(0) = calib(4);
+    tempD(1) = calib(5);
+    tempD(2) = calib(6);
+    tempD(3) = calib(7);
+    camera_d_OPENCV = tempD;
+  }
+
+  /**
+   * @brief Given a raw uv point, this will undistort it based on the camera matrices into normalized camera coords.
+   * @param uv_dist Raw uv coordinate we wish to undistort
+   * @return 2d vector of normalized coordinates
+   */
+  virtual Eigen::Vector2f undistort_f(const Eigen::Vector2f &uv_dist) = 0;
+
+  /**
+   * @brief Given a raw uv point, this will undistort it based on the camera matrices into normalized camera coords.
+   * @param uv_dist Raw uv coordinate we wish to undistort
+   * @return 2d vector of normalized coordinates
+   */
+  Eigen::Vector2d undistort_d(const Eigen::Vector2d &uv_dist) {
+    Eigen::Vector2f ept1, ept2;
+    ept1 = uv_dist.cast<float>();
+    ept2 = undistort_f(ept1);
+    return ept2.cast<double>();
+  }
+
+  /**
+   * @brief Given a raw uv point, this will undistort it based on the camera matrices into normalized camera coords.
+   * @param uv_dist Raw uv coordinate we wish to undistort
+   * @return 2d vector of normalized coordinates
+   */
+  cv::Point2f undistort_cv(const cv::Point2f &uv_dist) {
+    Eigen::Vector2f ept1, ept2;
+    ept1 << uv_dist.x, uv_dist.y;
+    ept2 = undistort_f(ept1);
+    cv::Point2f pt_out;
+    pt_out.x = ept2(0);
+    pt_out.y = ept2(1);
+    return pt_out;
+  }
+
+  /**
+   * @brief Given a normalized uv coordinate this will distort it to the raw image plane
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @return 2d vector of raw uv coordinate
+   */
+  virtual Eigen::Vector2f distort_f(const Eigen::Vector2f &uv_norm) = 0;
+
+  /**
+   * @brief Given a normalized uv coordinate this will distort it to the raw image plane
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @return 2d vector of raw uv coordinate
+   */
+  Eigen::Vector2d distort_d(const Eigen::Vector2d &uv_norm) {
+    Eigen::Vector2f ept1, ept2;
+    ept1 = uv_norm.cast<float>();
+    ept2 = distort_f(ept1);
+    return ept2.cast<double>();
+  }
+
+  /**
+   * @brief Given a normalized uv coordinate this will distort it to the raw image plane
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @return 2d vector of raw uv coordinate
+   */
+  cv::Point2f distort_cv(const cv::Point2f &uv_norm) {
+    Eigen::Vector2f ept1, ept2;
+    ept1 << uv_norm.x, uv_norm.y;
+    ept2 = distort_f(ept1);
+    cv::Point2f pt_out;
+    pt_out.x = ept2(0);
+    pt_out.y = ept2(1);
+    return pt_out;
+  }
+
+  /**
+   * @brief Computes the derivative of raw distorted to normalized coordinate.
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @param H_dz_dzn Derivative of measurement z in respect to normalized
+   * @param H_dz_dzeta Derivative of measurement z in respect to intrinic parameters
+   */
+  virtual void compute_distort_jacobian(const Eigen::Vector2d &uv_norm, Eigen::MatrixXd &H_dz_dzn, Eigen::MatrixXd &H_dz_dzeta) = 0;
+
+  /// Gets the complete intrinsic vector
+  Eigen::MatrixXd get_value() { return camera_values; }
+
+  /// Gets the camera matrix
+  cv::Matx33d get_K() { return camera_k_OPENCV; }
+
+  /// Gets the camera distortion
+  cv::Vec4d get_D() { return camera_d_OPENCV; }
+
+protected:
+  // Cannot construct the base camera class, needs a distortion model
+  CamBase() = default;
+
+  /// Raw set of camera intrinic values (f_x & f_y & c_x & c_y & k_1 & k_2 & k_3 & k_4)
+  Eigen::MatrixXd camera_values;
+
+  /// Camera intrinsics in OpenCV format
+  cv::Matx33d camera_k_OPENCV;
+
+  /// Camera distortion in OpenCV format
+  cv::Vec4d camera_d_OPENCV;
+};
+
+} // namespace ov_core
+
+#endif /* OV_CORE_CAM_BASE_H */
\ No newline at end of file
diff --git a/ov_core/src/cam/CamEqui.h b/ov_core/src/cam/CamEqui.h
new file mode 100644
index 000000000..abc44eaf6
--- /dev/null
+++ b/ov_core/src/cam/CamEqui.h
@@ -0,0 +1,229 @@
+/*
+ * OpenVINS: An Open Platform for Visual-Inertial Research
+ * Copyright (C) 2021 Patrick Geneva
+ * Copyright (C) 2021 Guoquan Huang
+ * Copyright (C) 2021 OpenVINS Contributors
+ * Copyright (C) 2019 Kevin Eckenhoff
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <https://www.gnu.org/licenses/>.
+ */
+
+#ifndef OV_CORE_CAM_EQUI_H
+#define OV_CORE_CAM_EQUI_H
+
+#include "CamBase.h"
+
+namespace ov_core {
+
+/**
+ * @brief Fisheye / equadistant model pinhole camera model class
+ *
+ * As fisheye or wide-angle lenses are widely used in practice, we here provide mathematical derivations
+ * of such distortion model as in [OpenCV fisheye](https://docs.opencv.org/3.4/db/d58/group__calib3d__fisheye.html#details).
+ *
+ * \f{align*}{
+ * \begin{bmatrix} u \\ v \end{bmatrix}:= \mathbf{z}_k &= \mathbf h_d(\mathbf{z}_{n,k}, ~\boldsymbol\zeta)
+ * = \begin{bmatrix}  f_x * x + c_x \\
+ * f_y * y + c_y \end{bmatrix}\\[1em]
+ * \empty
+ * {\rm where}~~
+ * x &= \frac{x_n}{r} * \theta_d \\
+ * y &= \frac{y_n}{r} * \theta_d \\
+ * \theta_d &= \theta (1 + k_1 \theta^2 + k_2 \theta^4 + k_3 \theta^6 + k_4 \theta^8) \\
+ * \quad r^2 &= x_n^2 + y_n^2 \\
+ * \theta &= atan(r)
+ * \f}
+ *
+ * where \f$ \mathbf{z}_{n,k} = [ x_n ~ y_n ]^\top\f$ are the normalized coordinates of the 3D feature
+ * and u and v are the distorted image coordinates on the image plane.
+ * Clearly, the following distortion intrinsic parameters are used in the above model:
+ *
+ * \f{align*}{
+ * \boldsymbol\zeta = \begin{bmatrix} f_x & f_y & c_x & c_y & k_1 & k_2 & k_3 & k_4 \end{bmatrix}^\top
+ * \f}
+ *
+ * In analogy to the previous radial distortion (see @ref ov_core::CamRadtan) case, the following Jacobian for these
+ * parameters is needed for intrinsic calibration:
+ * \f{align*}{
+ * \frac{\partial \mathbf h_d (\cdot)}{\partial \boldsymbol\zeta} =
+ * \begin{bmatrix}
+ * x_n & 0  & 1 & 0 & f_x*(\frac{x_n}{r}\theta^3) & f_x*(\frac{x_n}{r}\theta^5) & f_x*(\frac{x_n}{r}\theta^7) & f_x*(\frac{x_n}{r}\theta^9)
+ * \\[5pt] 0  & y_n & 0 & 1 & f_y*(\frac{y_n}{r}\theta^3) & f_y*(\frac{y_n}{r}\theta^5) & f_y*(\frac{y_n}{r}\theta^7) &
+ * f_y*(\frac{y_n}{r}\theta^9) \end{bmatrix} \f}
+ *
+ * Similarly, with the chain rule of differentiation,
+ * we can compute the following Jacobian with respect to the normalized coordinates:
+ *
+ * \f{align*}{
+ * \frac{\partial \mathbf h_d(\cdot)}{\partial \mathbf{z}_{n,k}}
+ * &=
+ * \frac{\partial uv}{\partial xy}\frac{\partial xy}{\partial x_ny_n}+
+ * \frac{\partial uv}{\partial xy}\frac{\partial xy}{\partial r}\frac{\partial r}{\partial x_ny_n}+
+ * \frac{\partial uv}{\partial xy}\frac{\partial xy}{\partial \theta_d}\frac{\partial \theta_d}{\partial \theta}\frac{\partial
+ * \theta}{\partial r}\frac{\partial r}{\partial x_ny_n} \\[1em] \empty
+ * {\rm where}~~~~
+ * \frac{\partial uv}{\partial xy} &= \begin{bmatrix} f_x & 0 \\ 0 & f_y \end{bmatrix} \\
+ * \empty
+ * \frac{\partial xy}{\partial x_ny_n} &= \begin{bmatrix} \theta_d/r & 0 \\ 0 & \theta_d/r \end{bmatrix} \\
+ * \empty
+ * \frac{\partial xy}{\partial r} &= \begin{bmatrix} -\frac{x_n}{r^2}\theta_d \\ -\frac{y_n}{r^2}\theta_d \end{bmatrix} \\
+ * \empty
+ * \frac{\partial r}{\partial x_ny_n} &= \begin{bmatrix} \frac{x_n}{r} & \frac{y_n}{r} \end{bmatrix} \\
+ * \empty
+ * \frac{\partial xy}{\partial \theta_d} &= \begin{bmatrix} \frac{x_n}{r} \\ \frac{y_n}{r} \end{bmatrix} \\
+ * \empty
+ * \frac{\partial \theta_d}{\partial \theta} &= \begin{bmatrix} 1 + 3k_1 \theta^2 + 5k_2 \theta^4 + 7k_3 \theta^6 + 9k_4
+ * \theta^8\end{bmatrix} \\ \empty \frac{\partial \theta}{\partial r} &= \begin{bmatrix} \frac{1}{r^2+1} \end{bmatrix} \f}
+ *
+ * To equate this to one of Kalibr's models, this is what you would use for `pinhole-equi`.
+ */
+class CamEqui : public CamBase {
+
+public:
+  // constructor
+  CamEqui() {}
+
+  /**
+   * @brief Given a raw uv point, this will undistort it based on the camera matrices into normalized camera coords.
+   * @param uv_dist Raw uv coordinate we wish to undistort
+   * @return 2d vector of normalized coordinates
+   */
+  Eigen::Vector2f undistort_f(const Eigen::Vector2f &uv_dist) override {
+
+    // Determine what camera parameters we should use
+    cv::Matx33d camK = camera_k_OPENCV;
+    cv::Vec4d camD = camera_d_OPENCV;
+
+    // Convert point to opencv format
+    cv::Mat mat(1, 2, CV_32F);
+    mat.at<float>(0, 0) = uv_dist(0);
+    mat.at<float>(0, 1) = uv_dist(1);
+    mat = mat.reshape(2); // Nx1, 2-channel
+
+    // Undistort it!
+    cv::fisheye::undistortPoints(mat, mat, camK, camD);
+
+    // Construct our return vector
+    Eigen::Vector2f pt_out;
+    mat = mat.reshape(1); // Nx2, 1-channel
+    pt_out(0) = mat.at<float>(0, 0);
+    pt_out(1) = mat.at<float>(0, 1);
+    return pt_out;
+  }
+
+  /**
+   * @brief Given a normalized uv coordinate this will distort it to the raw image plane
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @return 2d vector of raw uv coordinate
+   */
+  Eigen::Vector2f distort_f(const Eigen::Vector2f &uv_norm) override {
+
+    // Get our camera parameters
+    Eigen::MatrixXd cam_d = camera_values;
+
+    // Calculate distorted coordinates for fisheye
+    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
+    double theta = std::atan(r);
+    double theta_d = theta + cam_d(4) * std::pow(theta, 3) + cam_d(5) * std::pow(theta, 5) + cam_d(6) * std::pow(theta, 7) +
+                     cam_d(7) * std::pow(theta, 9);
+
+    // Handle when r is small (meaning our xy is near the camera center)
+    double inv_r = (r > 1e-8) ? 1.0 / r : 1.0;
+    double cdist = (r > 1e-8) ? theta_d * inv_r : 1.0;
+
+    // Calculate distorted coordinates for fisheye
+    Eigen::Vector2f uv_dist;
+    double x1 = uv_norm(0) * cdist;
+    double y1 = uv_norm(1) * cdist;
+    uv_dist(0) = (float)(cam_d(0) * x1 + cam_d(2));
+    uv_dist(1) = (float)(cam_d(1) * y1 + cam_d(3));
+    return uv_dist;
+  }
+
+  /**
+   * @brief Computes the derivative of raw distorted to normalized coordinate.
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @param H_dz_dzn Derivative of measurement z in respect to normalized
+   * @param H_dz_dzeta Derivative of measurement z in respect to intrinic parameters
+   */
+  void compute_distort_jacobian(const Eigen::Vector2d &uv_norm, Eigen::MatrixXd &H_dz_dzn, Eigen::MatrixXd &H_dz_dzeta) override {
+
+    // Get our camera parameters
+    Eigen::MatrixXd cam_d = camera_values;
+
+    // Calculate distorted coordinates for fisheye
+    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
+    double theta = std::atan(r);
+    double theta_d = theta + cam_d(4) * std::pow(theta, 3) + cam_d(5) * std::pow(theta, 5) + cam_d(6) * std::pow(theta, 7) +
+                     cam_d(7) * std::pow(theta, 9);
+
+    // Handle when r is small (meaning our xy is near the camera center)
+    double inv_r = (r > 1e-8) ? 1.0 / r : 1.0;
+    double cdist = (r > 1e-8) ? theta_d * inv_r : 1.0;
+
+    // Jacobian of distorted pixel to "normalized" pixel
+    Eigen::Matrix<double, 2, 2> duv_dxy = Eigen::Matrix<double, 2, 2>::Zero();
+    duv_dxy << cam_d(0), 0, 0, cam_d(1);
+
+    // Jacobian of "normalized" pixel to normalized pixel
+    Eigen::Matrix<double, 2, 2> dxy_dxyn = Eigen::Matrix<double, 2, 2>::Zero();
+    dxy_dxyn << theta_d * inv_r, 0, 0, theta_d * inv_r;
+
+    // Jacobian of "normalized" pixel to r
+    Eigen::Matrix<double, 2, 1> dxy_dr = Eigen::Matrix<double, 2, 1>::Zero();
+    dxy_dr << -uv_norm(0) * theta_d * inv_r * inv_r, -uv_norm(1) * theta_d * inv_r * inv_r;
+
+    // Jacobian of r pixel to normalized xy
+    Eigen::Matrix<double, 1, 2> dr_dxyn = Eigen::Matrix<double, 1, 2>::Zero();
+    dr_dxyn << uv_norm(0) * inv_r, uv_norm(1) * inv_r;
+
+    // Jacobian of "normalized" pixel to theta_d
+    Eigen::Matrix<double, 2, 1> dxy_dthd = Eigen::Matrix<double, 2, 1>::Zero();
+    dxy_dthd << uv_norm(0) * inv_r, uv_norm(1) * inv_r;
+
+    // Jacobian of theta_d to theta
+    double dthd_dth = 1 + 3 * cam_d(4) * std::pow(theta, 2) + 5 * cam_d(5) * std::pow(theta, 4) + 7 * cam_d(6) * std::pow(theta, 6) +
+                      9 * cam_d(7) * std::pow(theta, 8);
+
+    // Jacobian of theta to r
+    double dth_dr = 1 / (r * r + 1);
+
+    // Total Jacobian wrt normalized pixel coordinates
+    H_dz_dzn = Eigen::MatrixXd::Zero(2, 2);
+    H_dz_dzn = duv_dxy * (dxy_dxyn + (dxy_dr + dxy_dthd * dthd_dth * dth_dr) * dr_dxyn);
+
+    // Calculate distorted coordinates for fisheye
+    double x1 = uv_norm(0) * cdist;
+    double y1 = uv_norm(1) * cdist;
+
+    // Compute the Jacobian in respect to the intrinsics
+    H_dz_dzeta = Eigen::MatrixXd::Zero(2, 8);
+    H_dz_dzeta(0, 0) = x1;
+    H_dz_dzeta(0, 2) = 1;
+    H_dz_dzeta(0, 4) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 3);
+    H_dz_dzeta(0, 5) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 5);
+    H_dz_dzeta(0, 6) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 7);
+    H_dz_dzeta(0, 7) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 9);
+    H_dz_dzeta(1, 1) = y1;
+    H_dz_dzeta(1, 3) = 1;
+    H_dz_dzeta(1, 4) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 3);
+    H_dz_dzeta(1, 5) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 5);
+    H_dz_dzeta(1, 6) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 7);
+    H_dz_dzeta(1, 7) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 9);
+  }
+};
+
+} // namespace ov_core
+
+#endif /* OV_CORE_CAM_EQUI_H */
\ No newline at end of file
diff --git a/ov_core/src/cam/CamRadtan.h b/ov_core/src/cam/CamRadtan.h
new file mode 100644
index 000000000..0ee16d101
--- /dev/null
+++ b/ov_core/src/cam/CamRadtan.h
@@ -0,0 +1,199 @@
+/*
+ * OpenVINS: An Open Platform for Visual-Inertial Research
+ * Copyright (C) 2021 Patrick Geneva
+ * Copyright (C) 2021 Guoquan Huang
+ * Copyright (C) 2021 OpenVINS Contributors
+ * Copyright (C) 2019 Kevin Eckenhoff
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <https://www.gnu.org/licenses/>.
+ */
+
+#ifndef OV_CORE_CAM_RADTAN_H
+#define OV_CORE_CAM_RADTAN_H
+
+#include "CamBase.h"
+
+namespace ov_core {
+
+/**
+ * @brief Radial-tangential / Brown–Conrady model pinhole camera model class
+ *
+ * To calibrate camera intrinsics, we need to know how to map our normalized coordinates
+ * into the raw pixel coordinates on the image plane. We first employ the radial distortion
+ * as in [OpenCV model](https://docs.opencv.org/3.4/da/d54/group__imgproc__transform.html#details):
+ *
+ * \f{align*}{
+ * \begin{bmatrix} u \\ v \end{bmatrix}:= \mathbf{z}_k &= \mathbf h_d(\mathbf{z}_{n,k}, ~\boldsymbol\zeta)
+ * = \begin{bmatrix}  f_x * x + c_x \\
+ * f_y * y + c_y \end{bmatrix}\\[1em]
+ * \empty
+ * {\rm where}~~
+ * x &= x_n (1 + k_1 r^2 + k_2 r^4) + 2 p_1 x_n y_n + p_2(r^2 + 2 x_n^2) \\\
+ * y &= y_n (1 + k_1 r^2 + k_2 r^4) + p_1 (r^2 + 2 y_n^2) + 2 p_2 x_n y_n \\[1em]
+ * r^2 &= x_n^2 + y_n^2
+ * \f}
+ *
+ * where \f$ \mathbf{z}_{n,k} = [ x_n ~ y_n ]^\top\f$  are the normalized coordinates of the 3D feature and u and v are the distorted image
+ * coordinates on the image plane. The following distortion and camera intrinsic (focal length and image center) parameters are involved in
+ * the above distortion model, which can be estimated online:
+ *
+ * \f{align*}{
+ * \boldsymbol\zeta = \begin{bmatrix} f_x & f_y & c_x & c_y & k_1 & k_2 & p_1 & p_2 \end{bmatrix}^\top
+ * \f}
+ *
+ * Note that we do not estimate the higher order (i.e., higher than fourth order) terms as in most offline calibration
+ * methods such as [Kalibr](https://github.com/ethz-asl/kalibr). To estimate these intrinsic parameters (including the
+ * distortation parameters), the following Jacobian for these parameters is needed:
+ *
+ * \f{align*}{
+ * \frac{\partial \mathbf h_d(\cdot)}{\partial \boldsymbol\zeta} =
+ * \begin{bmatrix}
+ * x & 0  & 1 & 0 & f_x*(x_nr^2) & f_x*(x_nr^4) & f_x*(2x_ny_n) & f_x*(r^2+2x_n^2)  \\[5pt]
+ * 0  & y & 0 & 1 & f_y*(y_nr^2) & f_y*(y_nr^4) & f_y*(r^2+2y_n^2) & f_y*(2x_ny_n)
+ * \end{bmatrix}
+ * \f}
+ *
+ * Similarly, the Jacobian with respect to the normalized coordinates can be obtained as follows:
+ *
+ * \f{align*}{
+ * \frac{\partial \mathbf h_d (\cdot)}{\partial \mathbf{z}_{n,k}} =
+ * \begin{bmatrix}
+ * f_x*((1+k_1r^2+k_2r^4)+(2k_1x_n^2+4k_2x_n^2(x_n^2+y_n^2))+2p_1y_n+(2p_2x_n+4p_2x_n))  &
+ * f_x*(2k_1x_ny_n+4k_2x_ny_n(x_n^2+y_n^2)+2p_1x_n+2p_2y_n)    \\
+ * f_y*(2k_1x_ny_n+4k_2x_ny_n(x_n^2+y_n^2)+2p_1x_n+2p_2y_n)  &
+ * f_y*((1+k_1r^2+k_2r^4)+(2k_1y_n^2+4k_2y_n^2(x_n^2+y_n^2))+(2p_1y_n+4p_1y_n)+2p_2x_n)
+ * \end{bmatrix}
+ * \f}
+ *
+ * To equate this camera class to Kalibr's models, this is what you would use for `pinhole-radtan`.
+ *
+ */
+class CamRadtan : public CamBase {
+
+public:
+  /**
+   * Default constructor.
+   */
+  CamRadtan() {}
+
+  /**
+   * @brief Given a raw uv point, this will undistort it based on the camera matrices into normalized camera coords.
+   * @param uv_dist Raw uv coordinate we wish to undistort
+   * @return 2d vector of normalized coordinates
+   */
+  Eigen::Vector2f undistort_f(const Eigen::Vector2f &uv_dist) override {
+
+    // Determine what camera parameters we should use
+    cv::Matx33d camK = camera_k_OPENCV;
+    cv::Vec4d camD = camera_d_OPENCV;
+
+    // Convert to opencv format
+    cv::Mat mat(1, 2, CV_32F);
+    mat.at<float>(0, 0) = uv_dist(0);
+    mat.at<float>(0, 1) = uv_dist(1);
+    mat = mat.reshape(2); // Nx1, 2-channel
+
+    // Undistort it!
+    cv::undistortPoints(mat, mat, camK, camD);
+
+    // Construct our return vector
+    Eigen::Vector2f pt_out;
+    mat = mat.reshape(1); // Nx2, 1-channel
+    pt_out(0) = mat.at<float>(0, 0);
+    pt_out(1) = mat.at<float>(0, 1);
+    return pt_out;
+  }
+
+  /**
+   * @brief Given a normalized uv coordinate this will distort it to the raw image plane
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @return 2d vector of raw uv coordinate
+   */
+  Eigen::Vector2f distort_f(const Eigen::Vector2f &uv_norm) override {
+
+    // Get our camera parameters
+    Eigen::MatrixXd cam_d = camera_values;
+
+    // Calculate distorted coordinates for radial
+    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
+    double r_2 = r * r;
+    double r_4 = r_2 * r_2;
+    double x1 = uv_norm(0) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + 2 * cam_d(6) * uv_norm(0) * uv_norm(1) +
+                cam_d(7) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
+    double y1 = uv_norm(1) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + cam_d(6) * (r_2 + 2 * uv_norm(1) * uv_norm(1)) +
+                2 * cam_d(7) * uv_norm(0) * uv_norm(1);
+
+    // Return the distorted point
+    Eigen::Vector2f uv_dist;
+    uv_dist(0) = (float)(cam_d(0) * x1 + cam_d(2));
+    uv_dist(1) = (float)(cam_d(1) * y1 + cam_d(3));
+    return uv_dist;
+  }
+
+  /**
+   * @brief Computes the derivative of raw distorted to normalized coordinate.
+   * @param uv_norm Normalized coordinates we wish to distort
+   * @param H_dz_dzn Derivative of measurement z in respect to normalized
+   * @param H_dz_dzeta Derivative of measurement z in respect to intrinic parameters
+   */
+  void compute_distort_jacobian(const Eigen::Vector2d &uv_norm, Eigen::MatrixXd &H_dz_dzn, Eigen::MatrixXd &H_dz_dzeta) override {
+
+    // Get our camera parameters
+    Eigen::MatrixXd cam_d = camera_values;
+
+    // Calculate distorted coordinates for radial
+    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
+    double r_2 = r * r;
+    double r_4 = r_2 * r_2;
+
+    // Jacobian of distorted pixel to normalized pixel
+    H_dz_dzn = Eigen::MatrixXd::Zero(2, 2);
+    double x = uv_norm(0);
+    double y = uv_norm(1);
+    double x_2 = uv_norm(0) * uv_norm(0);
+    double y_2 = uv_norm(1) * uv_norm(1);
+    double x_y = uv_norm(0) * uv_norm(1);
+    H_dz_dzn(0, 0) = cam_d(0) * ((1 + cam_d(4) * r_2 + cam_d(5) * r_4) + (2 * cam_d(4) * x_2 + 4 * cam_d(5) * x_2 * r_2) +
+                                 2 * cam_d(6) * y + (2 * cam_d(7) * x + 4 * cam_d(7) * x));
+    H_dz_dzn(0, 1) = cam_d(0) * (2 * cam_d(4) * x_y + 4 * cam_d(5) * x_y * r_2 + 2 * cam_d(6) * x + 2 * cam_d(7) * y);
+    H_dz_dzn(1, 0) = cam_d(1) * (2 * cam_d(4) * x_y + 4 * cam_d(5) * x_y * r_2 + 2 * cam_d(6) * x + 2 * cam_d(7) * y);
+    H_dz_dzn(1, 1) = cam_d(1) * ((1 + cam_d(4) * r_2 + cam_d(5) * r_4) + (2 * cam_d(4) * y_2 + 4 * cam_d(5) * y_2 * r_2) +
+                                 2 * cam_d(7) * x + (2 * cam_d(6) * y + 4 * cam_d(6) * y));
+
+    // Calculate distorted coordinates for radtan
+    double x1 = uv_norm(0) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + 2 * cam_d(6) * uv_norm(0) * uv_norm(1) +
+                cam_d(7) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
+    double y1 = uv_norm(1) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + cam_d(6) * (r_2 + 2 * uv_norm(1) * uv_norm(1)) +
+                2 * cam_d(7) * uv_norm(0) * uv_norm(1);
+
+    // Compute the Jacobian in respect to the intrinsics
+    H_dz_dzeta = Eigen::MatrixXd::Zero(2, 8);
+    H_dz_dzeta(0, 0) = x1;
+    H_dz_dzeta(0, 2) = 1;
+    H_dz_dzeta(0, 4) = cam_d(0) * uv_norm(0) * r_2;
+    H_dz_dzeta(0, 5) = cam_d(0) * uv_norm(0) * r_4;
+    H_dz_dzeta(0, 6) = 2 * cam_d(0) * uv_norm(0) * uv_norm(1);
+    H_dz_dzeta(0, 7) = cam_d(0) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
+    H_dz_dzeta(1, 1) = y1;
+    H_dz_dzeta(1, 3) = 1;
+    H_dz_dzeta(1, 4) = cam_d(1) * uv_norm(1) * r_2;
+    H_dz_dzeta(1, 5) = cam_d(1) * uv_norm(1) * r_4;
+    H_dz_dzeta(1, 6) = cam_d(1) * (r_2 + 2 * uv_norm(1) * uv_norm(1));
+    H_dz_dzeta(1, 7) = 2 * cam_d(1) * uv_norm(0) * uv_norm(1);
+  }
+};
+
+} // namespace ov_core
+
+#endif /* OV_CORE_CAM_RADTAN_H */
\ No newline at end of file
diff --git a/ov_core/src/dummy.cpp b/ov_core/src/dummy.cpp
index 7fc9c1974..850e49e5f 100644
--- a/ov_core/src/dummy.cpp
+++ b/ov_core/src/dummy.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 /**
  * @namespace ov_core
  *
diff --git a/ov_core/src/feat/Feature.cpp b/ov_core/src/feat/Feature.cpp
index bca4b2c7b..a1f6958fe 100644
--- a/ov_core/src/feat/Feature.cpp
+++ b/ov_core/src/feat/Feature.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "Feature.h"
 
 using namespace ov_core;
@@ -110,4 +109,3 @@ void Feature::clean_older_measurements(double timestamp) {
     }
   }
 }
-
diff --git a/ov_core/src/feat/Feature.h b/ov_core/src/feat/Feature.h
index 6d8416169..98b3ea253 100644
--- a/ov_core/src/feat/Feature.h
+++ b/ov_core/src/feat/Feature.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_FEATURE_H
 #define OV_CORE_FEATURE_H
 
diff --git a/ov_core/src/feat/FeatureDatabase.h b/ov_core/src/feat/FeatureDatabase.h
index cad404e31..d272dc997 100644
--- a/ov_core/src/feat/FeatureDatabase.h
+++ b/ov_core/src/feat/FeatureDatabase.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_FEATURE_DATABASE_H
 #define OV_CORE_FEATURE_DATABASE_H
 
@@ -139,11 +138,11 @@ class FeatureDatabase {
         continue;
       }
       // Loop through each camera
+      // If we have a measurement greater-than or equal to the specified, this measurement is find
       bool has_newer_measurement = false;
       for (auto const &pair : (*it).second->timestamps) {
-        // If we have a measurement greater-than or equal to the specified, this measurement is find
-        if (!pair.second.empty() && pair.second.at(pair.second.size() - 1) >= timestamp) {
-          has_newer_measurement = true;
+        has_newer_measurement = (!pair.second.empty() && pair.second.at(pair.second.size() - 1) >= timestamp);
+        if (has_newer_measurement) {
           break;
         }
       }
@@ -186,10 +185,11 @@ class FeatureDatabase {
         continue;
       }
       // Loop through each camera
+      // Check if we have at least one time older then the requested
       bool found_containing_older = false;
       for (auto const &pair : (*it).second->timestamps) {
-        if (!pair.second.empty() && pair.second.at(0) < timestamp) {
-          found_containing_older = true;
+        found_containing_older = (!pair.second.empty() && pair.second.at(0) < timestamp);
+        if (found_containing_older) {
           break;
         }
       }
@@ -232,16 +232,10 @@ class FeatureDatabase {
         continue;
       }
       // Boolean if it has the timestamp
+      // Break out if we found a single timestamp that is equal to the specified time
       bool has_timestamp = false;
       for (auto const &pair : (*it).second->timestamps) {
-        // Loop through all timestamps, and see if it has it
-        for (auto &timefeat : pair.second) {
-          if (timefeat == timestamp) {
-            has_timestamp = true;
-            break;
-          }
-        }
-        // Break out if we found a single timestamp that is equal to the specified time
+        has_timestamp = (std::find(pair.second.begin(), pair.second.end(), timestamp) != pair.second.end());
         if (has_timestamp) {
           break;
         }
@@ -272,21 +266,17 @@ class FeatureDatabase {
    * If a feature was unable to be used, it will still remain since it will not have a delete flag set
    */
   void cleanup() {
-    // Debug
-    // int sizebefore = (int)features_idlookup.size();
     // Loop through all features
+    // int sizebefore = (int)features_idlookup.size();
     std::unique_lock<std::mutex> lck(mtx);
     for (auto it = features_idlookup.begin(); it != features_idlookup.end();) {
       // If delete flag is set, then delete it
-      // NOTE: if we are using a shared pointer, then no need to do this!
       if ((*it).second->to_delete) {
-        // delete (*it).second;
         features_idlookup.erase(it++);
       } else {
         it++;
       }
     }
-    // Debug
     // std::cout << "feat db = " << sizebefore << " -> " << (int)features_idlookup.size() << std::endl;
   }
 
@@ -301,12 +291,10 @@ class FeatureDatabase {
       // Count how many measurements
       int ct_meas = 0;
       for (const auto &pair : (*it).second->timestamps) {
-        ct_meas += (*it).second->timestamps.at(pair.first).size();
+        ct_meas += (int)(pair.second.size());
       }
       // If delete flag is set, then delete it
-      // NOTE: if we are using a shared pointer, then no need to do this!
       if (ct_meas < 1) {
-        // delete (*it).second;
         features_idlookup.erase(it++);
       } else {
         it++;
@@ -326,12 +314,10 @@ class FeatureDatabase {
       // Count how many measurements
       int ct_meas = 0;
       for (const auto &pair : (*it).second->timestamps) {
-        ct_meas += (*it).second->timestamps.at(pair.first).size();
+        ct_meas += (int)(pair.second.size());
       }
       // If delete flag is set, then delete it
-      // NOTE: if we are using a shared pointer, then no need to do this!
       if (ct_meas < 1) {
-        // delete (*it).second;
         features_idlookup.erase(it++);
       } else {
         it++;
diff --git a/ov_core/src/feat/FeatureInitializer.cpp b/ov_core/src/feat/FeatureInitializer.cpp
index a78043b77..f176c5c98 100644
--- a/ov_core/src/feat/FeatureInitializer.cpp
+++ b/ov_core/src/feat/FeatureInitializer.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "FeatureInitializer.h"
 
 using namespace ov_core;
@@ -89,6 +88,7 @@ bool FeatureInitializer::single_triangulation(Feature *feat, std::unordered_map<
   singularValues.resize(svd.singularValues().rows(), 1);
   singularValues = svd.singularValues();
   double condA = singularValues(0, 0) / singularValues(singularValues.rows() - 1, 0);
+  // std::cout << feat->featid << " - cond " << std::abs(condA) << " - z " << p_f(2, 0) << std::endl;
 
   // If we have a bad condition number, or it is too close
   // Then set the flag for bad (i.e. set z-axis to nan)
@@ -345,6 +345,7 @@ bool FeatureInitializer::single_gaussnewton(Feature *feat, std::unordered_map<si
         base_line_max = base_line;
     }
   }
+  // std::cout << feat->featid << " - max base " << (feat->p_FinA.norm() / base_line_max) << " - z " << feat->p_FinA(2) << std::endl;
 
   // Check if this feature is bad or not
   // 1. If the feature is too close
diff --git a/ov_core/src/feat/FeatureInitializer.h b/ov_core/src/feat/FeatureInitializer.h
index bd9e10a22..4c8312377 100644
--- a/ov_core/src/feat/FeatureInitializer.h
+++ b/ov_core/src/feat/FeatureInitializer.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OPEN_VINS_FEATUREINITIALIZER_H
 #define OPEN_VINS_FEATUREINITIALIZER_H
 
diff --git a/ov_core/src/feat/FeatureInitializerOptions.h b/ov_core/src/feat/FeatureInitializerOptions.h
index c252c7d7c..bb83f04a7 100644
--- a/ov_core/src/feat/FeatureInitializerOptions.h
+++ b/ov_core/src/feat/FeatureInitializerOptions.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_INITIALIZEROPTIONS_H
 #define OV_CORE_INITIALIZEROPTIONS_H
 
diff --git a/ov_core/src/init/InertialInitializer.cpp b/ov_core/src/init/InertialInitializer.cpp
index c3032bf0c..e7e471510 100644
--- a/ov_core/src/init/InertialInitializer.cpp
+++ b/ov_core/src/init/InertialInitializer.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "InertialInitializer.h"
 
 using namespace ov_core;
@@ -50,7 +49,7 @@ bool InertialInitializer::initialize_with_imu(double &time0, Eigen::Matrix<doubl
   double oldesttime = imu_data.at(0).timestamp;
 
   // Return if we don't have enough for two windows
-  if(newesttime-oldesttime < 2 * _window_length) {
+  if (newesttime - oldesttime < 2 * _window_length) {
     // printf(YELLOW "[INIT-IMU]: unable to select window of IMU readings, not enough readings\n" RESET);
     return false;
   }
@@ -98,7 +97,7 @@ bool InertialInitializer::initialize_with_imu(double &time0, Eigen::Matrix<doubl
     a_var_2to1 += (data.am - a_avg_2to1).dot(data.am - a_avg_2to1);
   }
   a_var_2to1 = std::sqrt(a_var_2to1 / ((int)window_2to1.size() - 1));
-  //printf(BOLDGREEN "[INIT-IMU]: IMU excitation, %.4f,%.4f\n" RESET, a_var_1to0, a_var_2to1);
+  // printf(BOLDGREEN "[INIT-IMU]: IMU excitation, %.4f,%.4f\n" RESET, a_var_1to0, a_var_2to1);
 
   // If it is below the threshold and we want to wait till we detect a jerk
   if (a_var_1to0 < _imu_excite_threshold && wait_for_jerk) {
@@ -116,7 +115,8 @@ bool InertialInitializer::initialize_with_imu(double &time0, Eigen::Matrix<doubl
   // If it is above the threshold and we are not waiting for a jerk
   // Then we are not stationary (i.e. moving) so we should wait till we are
   if ((a_var_1to0 > _imu_excite_threshold || a_var_2to1 > _imu_excite_threshold) && !wait_for_jerk) {
-    printf(YELLOW "[INIT-IMU]: to much IMU excitation, above threshold %.4f,%.4f > %.4f\n" RESET, a_var_1to0, a_var_2to1, _imu_excite_threshold);
+    printf(YELLOW "[INIT-IMU]: to much IMU excitation, above threshold %.4f,%.4f > %.4f\n" RESET, a_var_1to0, a_var_2to1,
+           _imu_excite_threshold);
     return false;
   }
 
diff --git a/ov_core/src/init/InertialInitializer.h b/ov_core/src/init/InertialInitializer.h
index 441003209..1ee8ccd42 100644
--- a/ov_core/src/init/InertialInitializer.h
+++ b/ov_core/src/init/InertialInitializer.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_INERTIALINITIALIZER_H
 #define OV_CORE_INERTIALINITIALIZER_H
 
diff --git a/ov_core/src/sim/BsplineSE3.cpp b/ov_core/src/sim/BsplineSE3.cpp
index 9e1e35641..9069bbb8d 100644
--- a/ov_core/src/sim/BsplineSE3.cpp
+++ b/ov_core/src/sim/BsplineSE3.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "BsplineSE3.h"
 
 using namespace ov_core;
diff --git a/ov_core/src/sim/BsplineSE3.h b/ov_core/src/sim/BsplineSE3.h
index cfdff9643..8d3e68fca 100644
--- a/ov_core/src/sim/BsplineSE3.h
+++ b/ov_core/src/sim/BsplineSE3.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_BSPLINESE3_H
 #define OV_CORE_BSPLINESE3_H
 
diff --git a/ov_core/src/test_tracking.cpp b/ov_core/src/test_tracking.cpp
index 21ca492f2..fc3f8b26f 100644
--- a/ov_core/src/test_tracking.cpp
+++ b/ov_core/src/test_tracking.cpp
@@ -19,11 +19,8 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include <cmath>
 #include <deque>
-#include <fstream>
-#include <iomanip>
 #include <sstream>
 #include <unistd.h>
 #include <vector>
@@ -37,9 +34,7 @@
 #include <opencv2/core/core.hpp>
 #include <opencv2/highgui/highgui.hpp>
 
-#include <boost/date_time/posix_time/posix_time.hpp>
-#include <boost/filesystem.hpp>
-
+#include "cam/CamRadtan.h"
 #include "track/TrackAruco.h"
 #include "track/TrackDescriptor.h"
 #include "track/TrackKLT.h"
@@ -60,7 +55,7 @@ std::deque<double> clonetimes;
 ros::Time time_start;
 
 // Our master function for tracking
-void handle_stereo(double time0, double time1, cv::Mat img0, cv::Mat img1, bool use_stereo);
+void handle_stereo(double time0, double time1, cv::Mat img0, cv::Mat img1);
 
 // Main function
 int main(int argc, char **argv) {
@@ -76,7 +71,7 @@ int main(int argc, char **argv) {
   // Location of the ROS bag we want to read in
   std::string path_to_bag;
   nh.param<std::string>("path_bag", path_to_bag, "/home/patrick/datasets/eth/V1_01_easy.bag");
-  // nh.param<std::string>("path_bag", path_to_bag, "/home/patrick/datasets/eth/V2_03_difficult.bag");
+  // nh.param<std::string>("path_bag", path_to_bag, "/home/patrick/datasets/open_vins/aruco_room_01.bag");
   printf("ros bag path is: %s\n", path_to_bag.c_str());
 
   // Get our start location and how much of the bag we want to play
@@ -90,17 +85,18 @@ int main(int argc, char **argv) {
   //===================================================================================
 
   // Parameters for our extractor
+  ov_core::TrackBase::HistogramMethod method = ov_core::TrackBase::HistogramMethod::NONE;
   int num_pts, num_aruco, fast_threshold, grid_x, grid_y, min_px_dist;
   double knn_ratio;
   bool do_downsizing, use_stereo;
-  nh.param<int>("num_pts", num_pts, 800);
+  nh.param<int>("num_pts", num_pts, 400);
   nh.param<int>("num_aruco", num_aruco, 1024);
   nh.param<int>("clone_states", clone_states, 11);
   nh.param<int>("fast_threshold", fast_threshold, 10);
   nh.param<int>("grid_x", grid_x, 9);
   nh.param<int>("grid_y", grid_y, 7);
-  nh.param<int>("min_px_dist", min_px_dist, 3);
-  nh.param<double>("knn_ratio", knn_ratio, 0.85);
+  nh.param<int>("min_px_dist", min_px_dist, 10);
+  nh.param<double>("knn_ratio", knn_ratio, 0.70);
   nh.param<bool>("downsize_aruco", do_downsizing, false);
   nh.param<bool>("use_stereo", use_stereo, false);
 
@@ -114,22 +110,20 @@ int main(int argc, char **argv) {
   printf("downsize aruco image: %d\n", do_downsizing);
 
   // Fake camera info (we don't need this, as we are not using the normalized coordinates for anything)
-  Eigen::Matrix<double, 8, 1> cam0_calib;
-  cam0_calib << 1, 1, 0, 0, 0, 0, 0, 0;
-
-  // Create our n-camera vectors
-  std::map<size_t, bool> camera_fisheye;
-  std::map<size_t, Eigen::VectorXd> camera_calibration;
-  camera_fisheye.insert({0, false});
-  camera_calibration.insert({0, cam0_calib});
-  camera_fisheye.insert({1, false});
-  camera_calibration.insert({1, cam0_calib});
+  std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras;
+  for (int i = 0; i < 2; i++) {
+    Eigen::Matrix<double, 8, 1> cam0_calib;
+    cam0_calib << 1, 1, 0, 0, 0, 0, 0, 0;
+    std::shared_ptr<CamBase> camera_calib = std::make_shared<CamRadtan>();
+    camera_calib->set_value(cam0_calib);
+    cameras.insert({i, camera_calib});
+  }
 
   // Lets make a feature extractor
-  extractor = new TrackKLT(num_pts, num_aruco, fast_threshold, grid_x, grid_y, min_px_dist);
-  // extractor = new TrackDescriptor(num_pts,num_aruco,true,fast_threshold,grid_x,grid_y,knn_ratio);
-  // extractor = new TrackAruco(num_aruco,true,do_downsizing);
-  extractor->set_calibration(camera_calibration, camera_fisheye);
+  //extractor = new TrackKLT(cameras, num_pts, num_aruco, !use_stereo, method, fast_threshold, grid_x, grid_y, min_px_dist);
+  // extractor = new TrackDescriptor(cameras, num_pts, num_aruco, !use_stereo, method, fast_threshold, grid_x, grid_y, min_px_dist,
+  // knn_ratio);
+  extractor = new TrackAruco(cameras, num_aruco, !use_stereo, method, do_downsizing);
 
   //===================================================================================
   //===================================================================================
@@ -217,7 +211,7 @@ int main(int argc, char **argv) {
     // If we have both left and right, then process
     if (has_left && has_right) {
       // process
-      handle_stereo(time0, time1, img0, img1, use_stereo);
+      handle_stereo(time0, time1, img0, img1);
       // reset bools
       has_left = false;
       has_right = false;
@@ -231,20 +225,41 @@ int main(int argc, char **argv) {
 /**
  * This function will process the new stereo pair with the extractor!
  */
-void handle_stereo(double time0, double time1, cv::Mat img0, cv::Mat img1, bool use_stereo) {
+void handle_stereo(double time0, double time1, cv::Mat img0, cv::Mat img1) {
+
+  // Animate our dynamic mask moving
+  // Very simple ball bounding around the screen example
+  cv::Mat mask = cv::Mat::zeros(cv::Size(img0.cols, img0.rows), CV_8UC1);
+  static cv::Point2f ball_center;
+  static cv::Point2f ball_velocity;
+  if (ball_velocity.x == 0 || ball_velocity.y == 0) {
+    ball_center.x = (float)img0.cols / 2.0f;
+    ball_center.y = (float)img0.rows / 2.0f;
+    ball_velocity.x = 2.5;
+    ball_velocity.y = 2.5;
+  }
+  ball_center += ball_velocity;
+  if (ball_center.x < 0 || (int)ball_center.x > img0.cols)
+    ball_velocity.x *= -1;
+  if (ball_center.y < 0 || (int)ball_center.y > img0.rows)
+    ball_velocity.y *= -1;
+  cv::circle(mask, ball_center, 100, cv::Scalar(255), cv::FILLED);
 
   // Process this new image
-  if (use_stereo) {
-    extractor->feed_stereo(time0, img0, img1, 0, 1);
-  } else {
-    extractor->feed_monocular(time0, img0, 0);
-    extractor->feed_monocular(time0, img1, 1);
-  }
+  ov_core::CameraData message;
+  message.timestamp = time0;
+  message.sensor_ids.push_back(0);
+  message.sensor_ids.push_back(1);
+  message.images.push_back(img0);
+  message.images.push_back(img1);
+  message.masks.push_back(mask);
+  message.masks.push_back(mask);
+  extractor->feed_new_camera(message);
 
   // Display the resulting tracks
   cv::Mat img_active, img_history;
   extractor->display_active(img_active, 255, 0, 0, 0, 0, 255);
-  extractor->display_history(img_history, 0, 255, 255, 255, 255, 255);
+  extractor->display_history(img_history, 255, 255, 0, 255, 255, 255);
 
   // Show our image!
   cv::imshow("Active Tracks", img_active);
diff --git a/ov_core/src/test_webcam.cpp b/ov_core/src/test_webcam.cpp
index 23a0aa6bc..3f5032c11 100644
--- a/ov_core/src/test_webcam.cpp
+++ b/ov_core/src/test_webcam.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include <cmath>
 #include <deque>
 #include <fstream>
@@ -34,6 +33,7 @@
 #include <boost/date_time/posix_time/posix_time.hpp>
 #include <boost/filesystem.hpp>
 
+#include "cam/CamRadtan.h"
 #include "track/TrackAruco.h"
 #include "track/TrackDescriptor.h"
 #include "track/TrackKLT.h"
@@ -56,10 +56,12 @@ int main(int argc, char **argv) {
   int clone_states = 20;
   int fast_threshold = 10;
   int grid_x = 5;
-  int grid_y = 3;
-  int min_px_dist = 10;
+  int grid_y = 4;
+  int min_px_dist = 20;
   double knn_ratio = 0.85;
   bool do_downsizing = false;
+  bool use_stereo = false;
+  ov_core::TrackBase::HistogramMethod method = ov_core::TrackBase::HistogramMethod::NONE;
 
   // Parameters for our extractor
   app.add_option("--num_pts", num_pts, "Number of feature tracks");
@@ -89,22 +91,19 @@ int main(int argc, char **argv) {
   printf("downsize aruco image: %d\n", do_downsizing);
 
   // Fake camera info (we don't need this, as we are not using the normalized coordinates for anything)
-  Eigen::Matrix<double, 8, 1> cam0_calib;
-  cam0_calib << 1, 1, 0, 0, 0, 0, 0, 0;
-
-  // Create our n-camera vectors
-  std::map<size_t, bool> camera_fisheye;
-  std::map<size_t, Eigen::VectorXd> camera_calibration;
-  camera_fisheye.insert({0, false});
-  camera_calibration.insert({0, cam0_calib});
-  camera_fisheye.insert({1, false});
-  camera_calibration.insert({1, cam0_calib});
+  std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras;
+  for (int i = 0; i < 2; i++) {
+    Eigen::Matrix<double, 8, 1> cam0_calib;
+    cam0_calib << 1, 1, 0, 0, 0, 0, 0, 0;
+    std::shared_ptr<CamBase> camera_calib = std::make_shared<CamRadtan>();
+    camera_calib->set_value(cam0_calib);
+    cameras.insert({i, camera_calib});
+  }
 
   // Lets make a feature extractor
-  extractor = new TrackKLT(num_pts, num_aruco, fast_threshold, grid_x, grid_y, min_px_dist);
-  // extractor = new TrackDescriptor(num_pts,num_aruco,true,fast_threshold,grid_x,grid_y,knn_ratio);
-  // extractor = new TrackAruco(num_aruco,true,do_downsizing);
-  extractor->set_calibration(camera_calibration, camera_fisheye);
+  extractor = new TrackKLT(cameras, num_pts, num_aruco, !use_stereo, method, fast_threshold, grid_x, grid_y, min_px_dist);
+  // extractor = new TrackDescriptor(cameras, num_pts, num_aruco, !use_stereo, method, fast_threshold, grid_x, grid_y, min_px_dist,
+  // knn_ratio); extractor = new TrackAruco(cameras, num_aruco, !use_stereo, method, do_downsizing);
 
   //===================================================================================
   //===================================================================================
@@ -141,15 +140,20 @@ int main(int argc, char **argv) {
 
     // Convert to grayscale if not
     if (frame.channels() != 1)
-      cv::cvtColor(frame, frame, cv::COLOR_GRAY2RGB);
+      cv::cvtColor(frame, frame, cv::COLOR_RGB2GRAY);
 
     // Else lets track this image
-    extractor->feed_monocular(current_time, frame, 0);
+    ov_core::CameraData message;
+    message.timestamp = current_time;
+    message.sensor_ids.push_back(0);
+    message.images.push_back(frame);
+    message.masks.push_back(cv::Mat::zeros(cv::Size(frame.cols, frame.rows), CV_8UC1));
+    extractor->feed_new_camera(message);
 
     // Display the resulting tracks
     cv::Mat img_active, img_history;
     extractor->display_active(img_active, 255, 0, 0, 0, 0, 255);
-    extractor->display_history(img_history, 0, 255, 255, 255, 255, 255);
+    extractor->display_history(img_history, 255, 255, 0, 255, 255, 255);
 
     // Show our image!
     cv::imshow("Active Tracks", img_active);
diff --git a/ov_core/src/track/Grider_DOG.h b/ov_core/src/track/Grider_DOG.h
deleted file mode 100644
index 753c101ca..000000000
--- a/ov_core/src/track/Grider_DOG.h
+++ /dev/null
@@ -1,170 +0,0 @@
-/*
- * OpenVINS: An Open Platform for Visual-Inertial Research
- * Copyright (C) 2021 Patrick Geneva
- * Copyright (C) 2021 Guoquan Huang
- * Copyright (C) 2021 OpenVINS Contributors
- * Copyright (C) 2019 Kevin Eckenhoff
- *
- * This program is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program.  If not, see <https://www.gnu.org/licenses/>.
- */
-
-
-#ifndef OV_CORE_GRIDER_DOG_H
-#define OV_CORE_GRIDER_DOG_H
-
-#include <Eigen/Eigen>
-#include <iostream>
-#include <vector>
-
-#include <opencv2/core/core.hpp>
-#include <opencv2/highgui/highgui.hpp>
-
-namespace ov_core {
-
-/**
- * @brief Does Difference of Gaussian (DoG) in a grid pattern.
- *
- * This does "Difference of Gaussian" detection in a grid pattern to try to get good features.
- * We then pick the top features in each grid, and return the top features collected over the entire image.
- * This class hasn't been tested that much, as we normally use the Grider_FAST class instead.
- *
- * @m_class{m-block m-danger}
- *
- * @par Improve and Test This!
- *      If you are interested in using this grider, then please give it a try and test if for us.
- *      Please open a pull request with any impromements, or an issue if you have had any success.
- *      We still recommend the Grider_FAST class since that is what we normally use.
- *
- */
-class Grider_DOG {
-
-public:
-  /**
-   * @brief Compare keypoints based on their response value.
-   * @param first First keypoint
-   * @param second Second keypoint
-   *
-   * We want to have the keypoints with the highest values!
-   * See: https://stackoverflow.com/a/10910921
-   */
-  static bool compare_response(cv::KeyPoint first, cv::KeyPoint second) { return first.response > second.response; }
-
-  /**
-   * @brief For a given small image region this will do the Difference of Gaussian (DOG) detection
-   *
-   * Will return the vector of keypoints with the averaged response for that given UV.
-   * See: https://github.com/jrdi/opencv-examples/blob/master/dog/main.cpp
-   */
-  static void detect(const cv::Mat &img, std::vector<cv::KeyPoint> &pts, int ksize, float sigma_small, float sigma_big, float threshold) {
-
-    // Calculate the two kernels we will use
-    cv::Mat gauBig = cv::getGaussianKernel(ksize, sigma_big, CV_32F);
-    cv::Mat gauSmall = cv::getGaussianKernel(ksize, sigma_small, CV_32F);
-    cv::Mat DoG = gauSmall - gauBig;
-
-    // Apply the kernel to our image
-    cv::Mat img_filtered;
-    cv::sepFilter2D(img, img_filtered, CV_32F, DoG.t(), DoG);
-    img_filtered = cv::abs(img_filtered);
-
-    // Assert we are a grey scaled image
-    assert(img_filtered.channels() == 1);
-
-    // Loop through and record all points above our threshold
-    for (int j = 0; j < img_filtered.rows; j++) {
-      for (int i = 0; i < img_filtered.cols; i++) {
-        // Calculate the response at this u,v coordinate
-        float response = img_filtered.at<float>(j, i);
-        // Check to see if it is able our specified threshold
-        if (response >= threshold) {
-          cv::KeyPoint pt;
-          pt.pt.x = i;
-          pt.pt.y = j;
-          pt.response = response;
-          pts.push_back(pt);
-        }
-      }
-    }
-  }
-
-  /**
-   * @brief This function will perform grid extraction using Difference of Gaussian (DOG)
-   * @param img Image we will do FAST extraction on
-   * @param pts vector of extracted points we will return
-   * @param num_features max number of features we want to extract
-   * @param grid_x size of grid in the x-direction / u-direction
-   * @param grid_y size of grid in the y-direction / v-direction
-   * @param ksize kernel size
-   * @param sigma_small small gaussian sigma
-   * @param sigma_big big gaussian sigma
-   * @param threshold response threshold
-   *
-   * Given a specified grid size, this will try to extract fast features from each grid.
-   * It will then return the best from each grid in the return vector.
-   */
-  static void perform_griding(const cv::Mat &img, std::vector<cv::KeyPoint> &pts, int num_features, int grid_x, int grid_y, int ksize,
-                              float sigma_small, float sigma_big, float threshold) {
-
-    // Calculate the size our extraction boxes should be
-    int size_x = img.cols / grid_x;
-    int size_y = img.rows / grid_y;
-
-    // Make sure our sizes are not zero
-    assert(size_x > 0);
-    assert(size_y > 0);
-
-    // We want to have equally distributed features
-    auto num_features_grid = (int)(num_features / (grid_x * grid_y)) + 1;
-
-    // Lets loop through each grid and extract features
-    for (int x = 0; x < img.cols; x += size_x) {
-      for (int y = 0; y < img.rows; y += size_y) {
-
-        // Skip if we are out of bounds
-        if (x + size_x > img.cols || y + size_y > img.rows)
-          continue;
-
-        // Calculate where we should be extracting from
-        cv::Rect img_roi = cv::Rect(x, y, size_x, size_y);
-
-        // Extract DOG features for this part of the image
-        std::vector<cv::KeyPoint> pts_new;
-        Grider_DOG::detect(img(img_roi), pts_new, ksize, sigma_small, sigma_big, threshold);
-
-        // Now lets get the top number from this
-        std::sort(pts_new.begin(), pts_new.end(), Grider_DOG::compare_response);
-
-        // Debug print out the response values
-        // for (auto pt : pts_new) {
-        //    std::cout << pt.response << std::endl;
-        //}
-        // std::cout << "======================" << std::endl;
-
-        // Append the "best" ones to our vector
-        // Note that we need to "correct" the point u,v since we extracted it in a ROI
-        // So we should append the location of that ROI in the image
-        for (size_t i = 0; i < (size_t)num_features_grid && i < pts_new.size(); i++) {
-          cv::KeyPoint pt_cor = pts_new.at(i);
-          pt_cor.pt.x += x;
-          pt_cor.pt.y += y;
-          pts.push_back(pt_cor);
-        }
-      }
-    }
-  }
-};
-
-} // namespace ov_core
-
-#endif /* OV_CORE_GRIDER_DOG_H */
\ No newline at end of file
diff --git a/ov_core/src/track/Grider_FAST.h b/ov_core/src/track/Grider_FAST.h
index 0d02caef4..9abd222e1 100644
--- a/ov_core/src/track/Grider_FAST.h
+++ b/ov_core/src/track/Grider_FAST.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_GRIDER_FAST_H
 #define OV_CORE_GRIDER_FAST_H
 
@@ -60,6 +59,7 @@ class Grider_FAST {
   /**
    * @brief This function will perform grid extraction using FAST.
    * @param img Image we will do FAST extraction on
+   * @param mask Region of the image we do not want to extract features in (255 = do not detect features)
    * @param pts vector of extracted points we will return
    * @param num_features max number of features we want to extract
    * @param grid_x size of grid in the x-direction / u-direction
@@ -70,8 +70,8 @@ class Grider_FAST {
    * Given a specified grid size, this will try to extract fast features from each grid.
    * It will then return the best from each grid in the return vector.
    */
-  static void perform_griding(const cv::Mat &img, std::vector<cv::KeyPoint> &pts, int num_features, int grid_x, int grid_y, int threshold,
-                              bool nonmaxSuppression) {
+  static void perform_griding(const cv::Mat &img, const cv::Mat &mask, std::vector<cv::KeyPoint> &pts, int num_features, int grid_x,
+                              int grid_y, int threshold, bool nonmaxSuppression) {
 
     // Calculate the size our extraction boxes should be
     int size_x = img.cols / grid_x;
@@ -112,9 +112,20 @@ class Grider_FAST {
                       // Note that we need to "correct" the point u,v since we extracted it in a ROI
                       // So we should append the location of that ROI in the image
                       for (size_t i = 0; i < (size_t)num_features_grid && i < pts_new.size(); i++) {
+
+                        // Create keypoint
                         cv::KeyPoint pt_cor = pts_new.at(i);
                         pt_cor.pt.x += (float)x;
                         pt_cor.pt.y += (float)y;
+
+                        // Reject if out of bounds (shouldn't be possible...)
+                        if ((int)pt_cor.pt.x < 0 || (int)pt_cor.pt.x > img.cols || (int)pt_cor.pt.y < 0 || (int)pt_cor.pt.y > img.rows)
+                          continue;
+
+                        // Check if it is in the mask region
+                        // NOTE: mask has max value of 255 (white) if it should be removed
+                        if (mask.at<uint8_t>((int)pt_cor.pt.y, (int)pt_cor.pt.x) > 127)
+                          continue;
                         collection.at(r).push_back(pt_cor);
                       }
                     }
diff --git a/ov_core/src/track/TrackAruco.cpp b/ov_core/src/track/TrackAruco.cpp
index 5b2958f32..a7285feac 100644
--- a/ov_core/src/track/TrackAruco.cpp
+++ b/ov_core/src/track/TrackAruco.cpp
@@ -19,12 +19,39 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "TrackAruco.h"
 
 using namespace ov_core;
 
-void TrackAruco::feed_monocular(double timestamp, cv::Mat &imgin, size_t cam_id) {
+void TrackAruco::feed_new_camera(const CameraData &message) {
+
+  // Error check that we have all the data
+  if (message.sensor_ids.empty() || message.sensor_ids.size() != message.images.size() || message.images.size() != message.masks.size()) {
+    printf(RED "[ERROR]: MESSAGE DATA SIZES DO NOT MATCH OR EMPTY!!!\n" RESET);
+    printf(RED "[ERROR]:   - message.sensor_ids.size() = %zu\n" RESET, message.sensor_ids.size());
+    printf(RED "[ERROR]:   - message.images.size() = %zu\n" RESET, message.images.size());
+    printf(RED "[ERROR]:   - message.masks.size() = %zu\n" RESET, message.masks.size());
+    std::exit(EXIT_FAILURE);
+  }
+
+  // There is not such thing as stereo tracking for aruco
+  // Thus here we should just call the monocular version two times
+#if ENABLE_ARUCO_TAGS
+  size_t num_images = message.images.size();
+  parallel_for_(cv::Range(0, (int)num_images), LambdaBody([&](const cv::Range &range) {
+                  for (int i = range.start; i < range.end; i++) {
+                    perform_tracking(message.timestamp, message.images.at(i), message.sensor_ids.at(i), message.masks.at(i));
+                  }
+                }));
+#else
+    printf(RED "[ERROR]: you have not compiled with aruco tag support!!!\n" RESET);
+    std::exit(EXIT_FAILURE);
+#endif
+}
+
+#if ENABLE_ARUCO_TAGS
+
+void TrackAruco::perform_tracking(double timestamp, const cv::Mat &imgin, size_t cam_id, const cv::Mat &maskin) {
 
   // Start timing
   rT1 = boost::posix_time::microsec_clock::local_time();
@@ -34,7 +61,16 @@ void TrackAruco::feed_monocular(double timestamp, cv::Mat &imgin, size_t cam_id)
 
   // Histogram equalize
   cv::Mat img;
-  cv::equalizeHist(imgin, img);
+  if (histogram_method == HistogramMethod::HISTOGRAM) {
+    cv::equalizeHist(imgin, img);
+  } else if (histogram_method == HistogramMethod::CLAHE) {
+    double eq_clip_limit = 10.0;
+    cv::Size eq_win_size = cv::Size(8, 8);
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
+    clahe->apply(imgin, img);
+  } else {
+    img = imgin;
+  }
 
   // Clear the old data from the last timestep
   ids_aruco[cam_id].clear();
@@ -90,16 +126,23 @@ void TrackAruco::feed_monocular(double timestamp, cv::Mat &imgin, size_t cam_id)
       continue;
     // Assert we have 4 points (we will only use one of them)
     assert(corners[cam_id].at(i).size() == 4);
-    // Try to undistort the point
-    cv::Point2f npt_l = undistort_point(corners[cam_id].at(i).at(0), cam_id);
-    // Append to the ids vector and database
-    ids_new.push_back((size_t)ids_aruco[cam_id].at(i));
-    database->update_feature((size_t)ids_aruco[cam_id].at(i), timestamp, cam_id, corners[cam_id].at(i).at(0).x,
-                             corners[cam_id].at(i).at(0).y, npt_l.x, npt_l.y);
+    for (int n = 0; n < 4; n++) {
+      // Check if it is in the mask
+      // NOTE: mask has max value of 255 (white) if it should be
+      if (maskin.at<uint8_t>((int)corners[cam_id].at(i).at(n).y, (int)corners[cam_id].at(i).at(n).x) > 127)
+        continue;
+      // Try to undistort the point
+      cv::Point2f npt_l = camera_calib.at(cam_id)->undistort_cv(corners[cam_id].at(i).at(n));
+      // Append to the ids vector and database
+      ids_new.push_back((size_t)ids_aruco[cam_id].at(i) + n * max_tag_id);
+      database->update_feature((size_t)ids_aruco[cam_id].at(i) + n * max_tag_id, timestamp, cam_id, corners[cam_id].at(i).at(n).x,
+                               corners[cam_id].at(i).at(n).y, npt_l.x, npt_l.y);
+    }
   }
 
   // Move forward in time
-  img_last[cam_id] = img.clone();
+  img_last[cam_id] = img;
+  img_mask_last[cam_id] = maskin;
   ids_last[cam_id] = ids_new;
   rT3 = boost::posix_time::microsec_clock::local_time();
 
@@ -109,25 +152,16 @@ void TrackAruco::feed_monocular(double timestamp, cv::Mat &imgin, size_t cam_id)
   // (int)good_left.size()); printf("[TIME-ARUCO]: %.4f seconds for total\n",(rT3-rT1).total_microseconds() * 1e-6);
 }
 
-void TrackAruco::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_rightin, size_t cam_id_left, size_t cam_id_right) {
-
-  // There is not such thing as stereo tracking for aruco
-  // Thus here we should just call the monocular version two times
-  parallel_for_(cv::Range(0, 2), LambdaBody([&](const cv::Range &range) {
-                  for (int i = range.start; i < range.end; i++) {
-                    bool is_left = (i == 0);
-                    feed_monocular(timestamp, is_left ? img_leftin : img_rightin, is_left ? cam_id_left : cam_id_right);
-                  }
-                }));
-}
-
 void TrackAruco::display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2) {
 
   // Cache the images to prevent other threads from editing while we viz (which can be slow)
-  std::map<size_t, cv::Mat> img_last_cache;
+  std::map<size_t, cv::Mat> img_last_cache, img_mask_last_cache;
   for (auto const &pair : img_last) {
     img_last_cache.insert({pair.first, pair.second.clone()});
   }
+  for (auto const &pair : img_mask_last) {
+    img_mask_last_cache.insert({pair.first, pair.second.clone()});
+  }
 
   // Get the largest width and height
   int max_width = -1;
@@ -170,8 +204,14 @@ void TrackAruco::display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2
     auto txtpt = (is_small) ? cv::Point(10, 30) : cv::Point(30, 60);
     cv::putText(img_temp, "CAM:" + std::to_string((int)pair.first), txtpt, cv::FONT_HERSHEY_COMPLEX_SMALL, (is_small) ? 1.5 : 3.0,
                 cv::Scalar(0, 255, 0), 3);
+    // Overlay the mask
+    cv::Mat mask = cv::Mat::zeros(img_mask_last_cache[pair.first].rows, img_mask_last_cache[pair.first].cols, CV_8UC3);
+    mask.setTo(cv::Scalar(0, 0, 255), img_mask_last_cache[pair.first]);
+    cv::addWeighted(mask, 0.1, img_temp, 1.0, 0.0, img_temp);
     // Replace the output image
     img_temp.copyTo(img_out(cv::Rect(max_width * index_cam, 0, img_last_cache[pair.first].cols, img_last_cache[pair.first].rows)));
     index_cam++;
   }
 }
+
+#endif
\ No newline at end of file
diff --git a/ov_core/src/track/TrackAruco.h b/ov_core/src/track/TrackAruco.h
index 486dcfae6..fd99430c7 100644
--- a/ov_core/src/track/TrackAruco.h
+++ b/ov_core/src/track/TrackAruco.h
@@ -19,11 +19,12 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_TRACK_ARUCO_H
 #define OV_CORE_TRACK_ARUCO_H
 
+#if ENABLE_ARUCO_TAGS
 #include <opencv2/aruco.hpp>
+#endif
 
 #include "TrackBase.h"
 
@@ -39,46 +40,35 @@ namespace ov_core {
 class TrackAruco : public TrackBase {
 
 public:
-  /**
-   * @brief Public default constructor
-   */
-  TrackAruco() : TrackBase(), max_tag_id(1024), do_downsizing(false) {
-    aruco_dict = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
-    aruco_params = cv::aruco::DetectorParameters::create();
-    // aruco_params->cornerRefinementMethod = cv::aruco::CornerRefineMethod::CORNER_REFINE_SUBPIX; // people with newer opencv might fail
-    // here
-  }
-
   /**
    * @brief Public constructor with configuration variables
+   * @param cameras camera calibration object which has all camera intrinsics in it
    * @param numaruco the max id of the arucotags, we don't use any tags greater than this value even if we extract them
-   * @param do_downsizing we can scale the image by 1/2 to increase Aruco tag extraction speed
+   * @param binocular if we should do binocular feature tracking or stereo if there are multiple cameras
+   * @param histmethod what type of histogram pre-processing should be done (histogram eq?)
+   * @param downsize we can scale the image by 1/2 to increase Aruco tag extraction speed
    */
-  explicit TrackAruco(int numaruco, bool do_downsizing) : TrackBase(0, numaruco), max_tag_id(numaruco), do_downsizing(do_downsizing) {
+  explicit TrackAruco(std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras, int numaruco, bool binocular,
+                      HistogramMethod histmethod, bool downsize)
+      : TrackBase(cameras, 0, numaruco, binocular, histmethod), max_tag_id(numaruco), do_downsizing(downsize) {
+#if ENABLE_ARUCO_TAGS
     aruco_dict = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
     aruco_params = cv::aruco::DetectorParameters::create();
-    // aruco_params->cornerRefinementMethod = cv::aruco::CornerRefineMethod::CORNER_REFINE_SUBPIX; // people with newer opencv might fail
-    // here
+    // NOTE: people with newer opencv might fail here
+    // aruco_params->cornerRefinementMethod = cv::aruco::CornerRefineMethod::CORNER_REFINE_SUBPIX;
+#else
+    printf(RED "[ERROR]: you have not compiled with aruco tag support!!!\n" RESET);
+    std::exit(EXIT_FAILURE);
+#endif
   }
 
   /**
-   * @brief Process a new monocular image
-   * @param timestamp timestamp the new image occurred at
-   * @param img new cv:Mat grayscale image
-   * @param cam_id the camera id that this new image corresponds too
-   */
-  void feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) override;
-
-  /**
-   * @brief Process new stereo pair of images
-   * @param timestamp timestamp this pair occured at (stereo is synchronised)
-   * @param img_left first grayscaled image
-   * @param img_right second grayscaled image
-   * @param cam_id_left first image camera id
-   * @param cam_id_right second image camera id
+   * @brief Process a new image
+   * @param message Contains our timestamp, images, and camera ids
    */
-  void feed_stereo(double timestamp, cv::Mat &img_left, cv::Mat &img_right, size_t cam_id_left, size_t cam_id_right) override;
+  void feed_new_camera(const CameraData &message);
 
+#if ENABLE_ARUCO_TAGS
   /**
    * @brief We override the display equation so we can show the tags we extract.
    * @param img_out image to which we will overlayed features on
@@ -86,10 +76,19 @@ class TrackAruco : public TrackBase {
    * @param r2,g2,b2 second color to draw in
    */
   void display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2) override;
+#endif
 
 protected:
-  // Timing variables
-  boost::posix_time::ptime rT1, rT2, rT3, rT4, rT5, rT6, rT7;
+#if ENABLE_ARUCO_TAGS
+  /**
+   * @brief Process a new monocular image
+   * @param timestamp timestamp the new image occurred at
+   * @param imgin new cv:Mat grayscale image
+   * @param cam_id the camera id that this new image corresponds too
+   * @param maskin tracking mask for the given input image
+   */
+  void perform_tracking(double timestamp, const cv::Mat &imgin, size_t cam_id, const cv::Mat &maskin);
+#endif
 
   // Max tag ID we should extract from (i.e., number of aruco tags starting from zero)
   int max_tag_id;
@@ -97,18 +96,18 @@ class TrackAruco : public TrackBase {
   // If we should downsize the image
   bool do_downsizing;
 
+#if ENABLE_ARUCO_TAGS
   // Our dictionary that we will extract aruco tags with
   cv::Ptr<cv::aruco::Dictionary> aruco_dict;
 
   // Parameters the opencv extractor uses
   cv::Ptr<cv::aruco::DetectorParameters> aruco_params;
 
-  // Mutex for our ids_aruco, corners, rejects which we use for drawing
-  std::mutex mtx_aruco;
-
   // Our tag IDs and corner we will get from the extractor
   std::unordered_map<size_t, std::vector<int>> ids_aruco;
   std::unordered_map<size_t, std::vector<std::vector<cv::Point2f>>> corners, rejects;
+#endif
+
 };
 
 } // namespace ov_core
diff --git a/ov_core/src/track/TrackBase.cpp b/ov_core/src/track/TrackBase.cpp
index e152cf050..77246df1b 100644
--- a/ov_core/src/track/TrackBase.cpp
+++ b/ov_core/src/track/TrackBase.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "TrackBase.h"
 
 using namespace ov_core;
@@ -27,10 +26,13 @@ using namespace ov_core;
 void TrackBase::display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2) {
 
   // Cache the images to prevent other threads from editing while we viz (which can be slow)
-  std::map<size_t, cv::Mat> img_last_cache;
+  std::map<size_t, cv::Mat> img_last_cache, img_mask_last_cache;
   for (auto const &pair : img_last) {
     img_last_cache.insert({pair.first, pair.second.clone()});
   }
+  for (auto const &pair : img_mask_last) {
+    img_mask_last_cache.insert({pair.first, pair.second.clone()});
+  }
 
   // Get the largest width and height
   int max_width = -1;
@@ -84,6 +86,10 @@ void TrackBase::display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2,
     auto txtpt = (is_small) ? cv::Point(10, 30) : cv::Point(30, 60);
     cv::putText(img_temp, "CAM:" + std::to_string((int)pair.first), txtpt, cv::FONT_HERSHEY_COMPLEX_SMALL, (is_small) ? 1.5 : 3.0,
                 cv::Scalar(0, 255, 0), 3);
+    // Overlay the mask
+    cv::Mat mask = cv::Mat::zeros(img_mask_last_cache[pair.first].rows, img_mask_last_cache[pair.first].cols, CV_8UC3);
+    mask.setTo(cv::Scalar(0, 0, 255), img_mask_last_cache[pair.first]);
+    cv::addWeighted(mask, 0.1, img_temp, 1.0, 0.0, img_temp);
     // Replace the output image
     img_temp.copyTo(img_out(cv::Rect(max_width * index_cam, 0, img_last_cache[pair.first].cols, img_last_cache[pair.first].rows)));
     index_cam++;
@@ -93,10 +99,13 @@ void TrackBase::display_active(cv::Mat &img_out, int r1, int g1, int b1, int r2,
 void TrackBase::display_history(cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2, std::vector<size_t> highlighted) {
 
   // Cache the images to prevent other threads from editing while we viz (which can be slow)
-  std::map<size_t, cv::Mat> img_last_cache;
+  std::map<size_t, cv::Mat> img_last_cache, img_mask_last_cache;
   for (auto const &pair : img_last) {
     img_last_cache.insert({pair.first, pair.second.clone()});
   }
+  for (auto const &pair : img_mask_last) {
+    img_mask_last_cache.insert({pair.first, pair.second.clone()});
+  }
 
   // Get the largest width and height
   int max_width = -1;
@@ -181,6 +190,10 @@ void TrackBase::display_history(cv::Mat &img_out, int r1, int g1, int b1, int r2
     auto txtpt = (is_small) ? cv::Point(10, 30) : cv::Point(30, 60);
     cv::putText(img_temp, "CAM:" + std::to_string((int)pair.first), txtpt, cv::FONT_HERSHEY_COMPLEX_SMALL, (is_small) ? 1.5 : 3.0,
                 cv::Scalar(0, 255, 0), 3);
+    // Overlay the mask
+    cv::Mat mask = cv::Mat::zeros(img_mask_last_cache[pair.first].rows, img_mask_last_cache[pair.first].cols, CV_8UC3);
+    mask.setTo(cv::Scalar(0, 0, 255), img_mask_last_cache[pair.first]);
+    cv::addWeighted(mask, 0.1, img_temp, 1.0, 0.0, img_temp);
     // Replace the output image
     img_temp.copyTo(img_out(cv::Rect(max_width * index_cam, 0, img_last_cache[pair.first].cols, img_last_cache[pair.first].rows)));
     index_cam++;
diff --git a/ov_core/src/track/TrackBase.h b/ov_core/src/track/TrackBase.h
index 77fedf0f9..92c16dbb5 100644
--- a/ov_core/src/track/TrackBase.h
+++ b/ov_core/src/track/TrackBase.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_TRACK_BASE_H
 #define OV_CORE_TRACK_BASE_H
 
@@ -29,16 +28,17 @@
 #include <thread>
 #include <unordered_map>
 
-#include <boost/thread.hpp>
+#include <boost/date_time/posix_time/posix_time.hpp>
 #include <opencv2/core/core.hpp>
 #include <opencv2/highgui/highgui.hpp>
 #include <opencv2/opencv.hpp>
 
-#include "Grider_DOG.h"
 #include "Grider_FAST.h"
+#include "cam/CamBase.h"
 #include "feat/FeatureDatabase.h"
 #include "utils/colors.h"
 #include "utils/lambda_body.h"
+#include "utils/sensor_data.h"
 
 namespace ov_core {
 
@@ -72,152 +72,38 @@ class TrackBase {
 
 public:
   /**
-   * @brief Public default constructor
+   * @brief Desired pre-processing image method.
    */
-  TrackBase() : database(new FeatureDatabase()), num_features(200), currid(0) {}
+  enum HistogramMethod { NONE, HISTOGRAM, CLAHE };
 
   /**
    * @brief Public constructor with configuration variables
+   * @param cameras camera calibration object which has all camera intrinsics in it
    * @param numfeats number of features we want want to track (i.e. track 200 points from frame to frame)
    * @param numaruco the max id of the arucotags, so we ensure that we start our non-auroc features above this value
+   * @param stereo if we should do stereo feature tracking or binocular
+   * @param histmethod what type of histogram pre-processing should be done (histogram eq?)
    */
-  TrackBase(int numfeats, int numaruco) : database(new FeatureDatabase()), num_features(numfeats) {
-    // Our current feature ID should be larger then the number of aruco tags we have
-    currid = (size_t)numaruco + 1;
-  }
-
-  virtual ~TrackBase() {}
-
-  /**
-   * @brief Given a the camera intrinsic values, this will set what we should normalize points with.
-   * This will also update the feature database with corrected normalized values.
-   * Normally this would only be needed if we are optimizing our camera parameters, and thus should re-normalize.
-   * @param camera_calib Calibration parameters for all cameras [fx,fy,cx,cy,d1,d2,d3,d4]
-   * @param camera_fisheye Map of camera_id => bool if we should do radtan or fisheye distortion model
-   * @param correct_active If we should re-undistort active features in our database
-   */
-  void set_calibration(std::map<size_t, Eigen::VectorXd> camera_calib, std::map<size_t, bool> camera_fisheye, bool correct_active = false) {
-
-    // Assert vectors are equal
-    assert(camera_calib.size() == camera_fisheye.size());
-
+  TrackBase(std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras, int numfeats, int numaruco, bool stereo,
+            HistogramMethod histmethod)
+      : camera_calib(cameras), database(new FeatureDatabase()), num_features(numfeats), use_stereo(stereo), histogram_method(histmethod) {
+    // Our current feature ID should be larger then the number of aruco tags we have (each has 4 corners)
+    currid = 4 * (size_t)numaruco + 1;
     // Create our mutex array based on the number of cameras we have
     // See https://stackoverflow.com/a/24170141/7718197
     if (mtx_feeds.empty() || mtx_feeds.size() != camera_calib.size()) {
       std::vector<std::mutex> list(camera_calib.size());
       mtx_feeds.swap(list);
     }
-
-    // Initialize our mutex and camera intrinsic values if we are just starting up
-    // The number of cameras should not change over time, thus we just need to check if our initial data is empty
-    if (camera_k_OPENCV.empty() || camera_d_OPENCV.empty() || this->camera_fisheye.empty()) {
-      // Overwrite our fisheye calibration
-      this->camera_fisheye = camera_fisheye;
-      // Convert values to the OpenCV format
-      for (auto const &cam : camera_calib) {
-        // Assert we are of size eight
-        assert(cam.second.rows() == 8);
-        // Camera matrix
-        cv::Matx33d tempK;
-        tempK(0, 0) = cam.second(0);
-        tempK(0, 1) = 0;
-        tempK(0, 2) = cam.second(2);
-        tempK(1, 0) = 0;
-        tempK(1, 1) = cam.second(1);
-        tempK(1, 2) = cam.second(3);
-        tempK(2, 0) = 0;
-        tempK(2, 1) = 0;
-        tempK(2, 2) = 1;
-        camera_k_OPENCV.insert({cam.first, tempK});
-        // Distortion parameters
-        cv::Vec4d tempD;
-        tempD(0) = cam.second(4);
-        tempD(1) = cam.second(5);
-        tempD(2) = cam.second(6);
-        tempD(3) = cam.second(7);
-        camera_d_OPENCV.insert({cam.first, tempD});
-      }
-      return;
-    }
-
-    // assert that the number of cameras can not change
-    assert(camera_k_OPENCV.size() == camera_calib.size());
-    assert(camera_k_OPENCV.size() == camera_fisheye.size());
-    assert(camera_k_OPENCV.size() == camera_d_OPENCV.size());
-
-    // Convert values to the OpenCV format
-    for (auto const &cam : camera_calib) {
-      // Lock this image feed
-      std::unique_lock<std::mutex> lck(mtx_feeds.at(cam.first));
-      // Fisheye value
-      this->camera_fisheye.at(cam.first) = camera_fisheye.at(cam.first);
-      // Assert we are of size eight
-      assert(cam.second.rows() == 8);
-      // Camera matrix
-      cv::Matx33d tempK;
-      tempK(0, 0) = cam.second(0);
-      tempK(0, 1) = 0;
-      tempK(0, 2) = cam.second(2);
-      tempK(1, 0) = 0;
-      tempK(1, 1) = cam.second(1);
-      tempK(1, 2) = cam.second(3);
-      tempK(2, 0) = 0;
-      tempK(2, 1) = 0;
-      tempK(2, 2) = 1;
-      camera_k_OPENCV.at(cam.first) = tempK;
-      // Distortion parameters
-      cv::Vec4d tempD;
-      tempD(0) = cam.second(4);
-      tempD(1) = cam.second(5);
-      tempD(2) = cam.second(6);
-      tempD(3) = cam.second(7);
-      camera_d_OPENCV.at(cam.first) = tempD;
-    }
-
-    // If we are calibrating camera intrinsics our normalize coordinates will be stale
-    // This is because we appended them to the database with the current best guess *at that timestep*
-    // Thus here since we have a change in calibration, re-normalize all the features we have
-    if (correct_active) {
-
-      // Get all features in this database
-      std::unordered_map<size_t, std::shared_ptr<Feature>> features_idlookup = database->get_internal_data();
-
-      // Loop through and correct each one
-      for (const auto &pair_feat : features_idlookup) {
-        // Get our feature
-        std::shared_ptr<Feature> feat = pair_feat.second;
-        // Loop through each camera for this feature
-        for (auto const &meas_pair : feat->timestamps) {
-          size_t camid = meas_pair.first;
-          std::unique_lock<std::mutex> lck(mtx_feeds.at(camid));
-          for (size_t m = 0; m < feat->uvs.at(camid).size(); m++) {
-            cv::Point2f pt(feat->uvs.at(camid).at(m)(0), feat->uvs.at(camid).at(m)(1));
-            cv::Point2f pt_n = undistort_point(pt, camid);
-            feat->uvs_norm.at(camid).at(m)(0) = pt_n.x;
-            feat->uvs_norm.at(camid).at(m)(1) = pt_n.y;
-          }
-        }
-      }
-    }
   }
 
-  /**
-   * @brief Process a new monocular image
-   * @param timestamp timestamp the new image occurred at
-   * @param img new cv:Mat grayscale image
-   * @param cam_id the camera id that this new image corresponds too
-   */
-  virtual void feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) = 0;
+  virtual ~TrackBase() {}
 
   /**
-   * @brief Process new stereo pair of images
-   * @param timestamp timestamp this pair occured at (stereo is synchronised)
-   * @param img_left first grayscaled image
-   * @param img_right second grayscaled image
-   * @param cam_id_left first image camera id
-   * @param cam_id_right second image camera id
+   * @brief Process a new image
+   * @param message Contains our timestamp, images, and camera ids
    */
-  virtual void feed_stereo(double timestamp, cv::Mat &img_left, cv::Mat &img_right, size_t cam_id_left, size_t cam_id_right) = 0;
+  virtual void feed_new_camera(const CameraData &message) = 0;
 
   /**
    * @brief Shows features extracted in the last image
@@ -232,7 +118,7 @@ class TrackBase {
    * @param img_out image to which we will overlayed features on
    * @param r1,g1,b1 first color to draw in
    * @param r2,g2,b2 second color to draw in
-   * @param highlighted unique ids which we wish to highlight
+   * @param highlighted unique ids which we wish to highlight (e.g. slam feats)
    */
   virtual void display_history(cv::Mat &img_out, int r1, int g1, int b1, int r2, int g2, int b2, std::vector<size_t> highlighted = {});
 
@@ -243,7 +129,11 @@ class TrackBase {
   std::shared_ptr<FeatureDatabase> get_feature_database() { return database; }
 
   /**
-   * @brief Changes the ID of an actively tracked feature to another one
+   * @brief Changes the ID of an actively tracked feature to another one.
+   *
+   * This function can be helpfull if you detect a loop-closure with an old frame.
+   * One could then change the id of an active feature to match the old feature id!
+   *
    * @param id_old Old id we want to change
    * @param id_new Id we want to change the old id to
    */
@@ -267,72 +157,9 @@ class TrackBase {
     }
   }
 
-  /**
-   * @brief Main function that will undistort/normalize a point.
-   * @param pt_in uv 2x1 point that we will undistort
-   * @param cam_id id of which camera this point is in
-   * @return undistorted 2x1 point
-   *
-   * Given a uv point, this will undistort it based on the camera matrices.
-   * This will call on the model needed, depending on what type of camera it is!
-   * So if we have fisheye for camera_1 is true, we will undistort with the fisheye model.
-   * In Kalibr's terms, the non-fisheye is `pinhole-radtan` while the fisheye is the `pinhole-equi` model.
-   */
-  cv::Point2f undistort_point(cv::Point2f pt_in, size_t cam_id) {
-    // Determine what camera parameters we should use
-    cv::Matx33d camK = this->camera_k_OPENCV.at(cam_id);
-    cv::Vec4d camD = this->camera_d_OPENCV.at(cam_id);
-    // Call on the fisheye if we should!
-    if (this->camera_fisheye.at(cam_id)) {
-      return undistort_point_fisheye(pt_in, camK, camD);
-    }
-    return undistort_point_brown(pt_in, camK, camD);
-  }
-
 protected:
-  /**
-   * @brief Undistort function RADTAN/BROWN.
-   *
-   * Given a uv point, this will undistort it based on the camera matrices.
-   * To equate this to Kalibr's models, this is what you would use for `pinhole-radtan`.
-   */
-  static cv::Point2f undistort_point_brown(cv::Point2f pt_in, cv::Matx33d &camK, cv::Vec4d &camD) {
-    // Convert to opencv format
-    cv::Mat mat(1, 2, CV_32F);
-    mat.at<float>(0, 0) = pt_in.x;
-    mat.at<float>(0, 1) = pt_in.y;
-    mat = mat.reshape(2); // Nx1, 2-channel
-    // Undistort it!
-    cv::undistortPoints(mat, mat, camK, camD);
-    // Construct our return vector
-    cv::Point2f pt_out;
-    mat = mat.reshape(1); // Nx2, 1-channel
-    pt_out.x = mat.at<float>(0, 0);
-    pt_out.y = mat.at<float>(0, 1);
-    return pt_out;
-  }
-
-  /**
-   * @brief Undistort function FISHEYE/EQUIDISTANT.
-   *
-   * Given a uv point, this will undistort it based on the camera matrices.
-   * To equate this to Kalibr's models, this is what you would use for `pinhole-equi`.
-   */
-  static cv::Point2f undistort_point_fisheye(cv::Point2f pt_in, cv::Matx33d &camK, cv::Vec4d &camD) {
-    // Convert point to opencv format
-    cv::Mat mat(1, 2, CV_32F);
-    mat.at<float>(0, 0) = pt_in.x;
-    mat.at<float>(0, 1) = pt_in.y;
-    mat = mat.reshape(2); // Nx1, 2-channel
-    // Undistort it!
-    cv::fisheye::undistortPoints(mat, mat, camK, camD);
-    // Construct our return vector
-    cv::Point2f pt_out;
-    mat = mat.reshape(1); // Nx2, 1-channel
-    pt_out.x = mat.at<float>(0, 0);
-    pt_out.y = mat.at<float>(0, 1);
-    return pt_out;
-  }
+  /// Camera object which has all calibration in it
+  std::unordered_map<size_t, std::shared_ptr<CamBase>> camera_calib;
 
   /// Database with all our current features
   std::shared_ptr<FeatureDatabase> database;
@@ -340,21 +167,24 @@ class TrackBase {
   /// If we are a fisheye model or not
   std::map<size_t, bool> camera_fisheye;
 
-  /// Camera intrinsics in OpenCV format
-  std::map<size_t, cv::Matx33d> camera_k_OPENCV;
-
-  /// Camera distortion in OpenCV format
-  std::map<size_t, cv::Vec4d> camera_d_OPENCV;
-
   /// Number of features we should try to track frame to frame
   int num_features;
 
+  /// If we should use binocular tracking or stereo tracking for multi-camera
+  bool use_stereo;
+
+  /// What histogram equalization method we should pre-process images with?
+  HistogramMethod histogram_method;
+
   /// Mutexs for our last set of image storage (img_last, pts_last, and ids_last)
   std::vector<std::mutex> mtx_feeds;
 
   /// Last set of images (use map so all trackers render in the same order)
   std::map<size_t, cv::Mat> img_last;
 
+  /// Last set of images (use map so all trackers render in the same order)
+  std::map<size_t, cv::Mat> img_mask_last;
+
   /// Last set of tracked points
   std::unordered_map<size_t, std::vector<cv::KeyPoint>> pts_last;
 
@@ -363,6 +193,9 @@ class TrackBase {
 
   /// Master ID for this tracker (atomic to allow for multi-threading)
   std::atomic<size_t> currid;
+
+  // Timing variables (most children use these...)
+  boost::posix_time::ptime rT1, rT2, rT3, rT4, rT5, rT6, rT7;
 };
 
 } // namespace ov_core
diff --git a/ov_core/src/track/TrackDescriptor.cpp b/ov_core/src/track/TrackDescriptor.cpp
index 30e78bd88..890faa23f 100644
--- a/ov_core/src/track/TrackDescriptor.cpp
+++ b/ov_core/src/track/TrackDescriptor.cpp
@@ -19,27 +19,68 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "TrackDescriptor.h"
 
 using namespace ov_core;
 
-void TrackDescriptor::feed_monocular(double timestamp, cv::Mat &imgin, size_t cam_id) {
+void TrackDescriptor::feed_new_camera(const CameraData &message) {
+
+  // Error check that we have all the data
+  if (message.sensor_ids.empty() || message.sensor_ids.size() != message.images.size() || message.images.size() != message.masks.size()) {
+    printf(RED "[ERROR]: MESSAGE DATA SIZES DO NOT MATCH OR EMPTY!!!\n" RESET);
+    printf(RED "[ERROR]:   - message.sensor_ids.size() = %zu\n" RESET, message.sensor_ids.size());
+    printf(RED "[ERROR]:   - message.images.size() = %zu\n" RESET, message.images.size());
+    printf(RED "[ERROR]:   - message.masks.size() = %zu\n" RESET, message.masks.size());
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Either call our stereo or monocular version
+  // If we are doing binocular tracking, then we should parallize our tracking
+  size_t num_images = message.images.size();
+  if (num_images == 1) {
+    feed_monocular(message, 0);
+  } else if (num_images == 2 && use_stereo) {
+    feed_stereo(message, 0, 1);
+  } else if (!use_stereo) {
+    parallel_for_(cv::Range(0, (int)num_images), LambdaBody([&](const cv::Range &range) {
+                    for (int i = range.start; i < range.end; i++) {
+                      feed_monocular(message, i);
+                    }
+                  }));
+  } else {
+    printf(RED "[ERROR]: invalid number of images passed %zu, we only support mono or stereo tracking", num_images);
+    std::exit(EXIT_FAILURE);
+  }
+}
+
+void TrackDescriptor::feed_monocular(const CameraData &message, size_t msg_id) {
 
   // Start timing
   rT1 = boost::posix_time::microsec_clock::local_time();
 
   // Lock this data feed for this camera
+  size_t cam_id = message.sensor_ids.at(msg_id);
   std::unique_lock<std::mutex> lck(mtx_feeds.at(cam_id));
 
   // Histogram equalize
-  cv::Mat img;
-  cv::equalizeHist(imgin, img);
+  cv::Mat img, mask;
+  if (histogram_method == HistogramMethod::HISTOGRAM) {
+    cv::equalizeHist(message.images.at(msg_id), img);
+  } else if (histogram_method == HistogramMethod::CLAHE) {
+    double eq_clip_limit = 10.0;
+    cv::Size eq_win_size = cv::Size(8, 8);
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
+    clahe->apply(message.images.at(msg_id), img);
+  } else {
+    img = message.images.at(msg_id);
+  }
+  mask = message.masks.at(msg_id);
 
   // If we are the first frame (or have lost tracking), initialize our descriptors
   if (pts_last.find(cam_id) == pts_last.end() || pts_last[cam_id].empty()) {
-    perform_detection_monocular(img, pts_last[cam_id], desc_last[cam_id], ids_last[cam_id]);
-    img_last[cam_id] = img.clone();
+    perform_detection_monocular(img, mask, pts_last[cam_id], desc_last[cam_id], ids_last[cam_id]);
+    img_last[cam_id] = img;
+    img_mask_last[cam_id] = mask;
     return;
   }
 
@@ -49,12 +90,9 @@ void TrackDescriptor::feed_monocular(double timestamp, cv::Mat &imgin, size_t ca
   std::vector<size_t> ids_new;
 
   // First, extract new descriptors for this new image
-  perform_detection_monocular(img, pts_new, desc_new, ids_new);
+  perform_detection_monocular(img, mask, pts_new, desc_new, ids_new);
   rT2 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Our matches temporally
   std::vector<cv::DMatch> matches_ll;
 
@@ -62,9 +100,6 @@ void TrackDescriptor::feed_monocular(double timestamp, cv::Mat &imgin, size_t ca
   robust_match(pts_last[cam_id], pts_new, desc_last[cam_id], desc_new, cam_id, cam_id, matches_ll);
   rT3 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Get our "good tracks"
   std::vector<cv::KeyPoint> good_left;
   std::vector<size_t> good_ids_left;
@@ -86,37 +121,31 @@ void TrackDescriptor::feed_monocular(double timestamp, cv::Mat &imgin, size_t ca
       }
     }
 
-    // If we found a good stereo track from left to left, and right to right
-    // Then lets replace the current ID with the old ID
-    // We also check that we are linked to the same past ID value
+    // Then lets replace the current ID with the old ID if found
+    // Else just append the current feature and its unique ID
+    good_left.push_back(pts_new[i]);
+    good_desc_left.push_back(desc_new.row((int)i));
     if (idll != -1) {
-      good_left.push_back(pts_new[i]);
-      good_desc_left.push_back(desc_new.row((int)i));
       good_ids_left.push_back(ids_last[cam_id][idll]);
       num_tracklast++;
     } else {
-      // Else just append the current feature and its unique ID
-      good_left.push_back(pts_new[i]);
-      good_desc_left.push_back(desc_new.row((int)i));
       good_ids_left.push_back(ids_new[i]);
     }
   }
   rT4 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Update our feature database, with theses new observations
   for (size_t i = 0; i < good_left.size(); i++) {
-    cv::Point2f npt_l = undistort_point(good_left.at(i).pt, cam_id);
-    database->update_feature(good_ids_left.at(i), timestamp, cam_id, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
+    cv::Point2f npt_l = camera_calib.at(cam_id)->undistort_cv(good_left.at(i).pt);
+    database->update_feature(good_ids_left.at(i), message.timestamp, cam_id, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
   }
 
   // Debug info
   // printf("LtoL = %d | good = %d | fromlast = %d\n",(int)matches_ll.size(),(int)good_left.size(),num_tracklast);
 
   // Move forward in time
-  img_last[cam_id] = img.clone();
+  img_last[cam_id] = img;
+  img_mask_last[cam_id] = mask;
   pts_last[cam_id] = good_left;
   ids_last[cam_id] = good_ids_left;
   desc_last[cam_id] = good_desc_left;
@@ -130,26 +159,44 @@ void TrackDescriptor::feed_monocular(double timestamp, cv::Mat &imgin, size_t ca
   // printf("[TIME-DESC]: %.4f seconds for total\n",(rT5-rT1).total_microseconds() * 1e-6);
 }
 
-void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_rightin, size_t cam_id_left, size_t cam_id_right) {
+void TrackDescriptor::feed_stereo(const CameraData &message, size_t msg_id_left, size_t msg_id_right) {
 
   // Start timing
   rT1 = boost::posix_time::microsec_clock::local_time();
 
   // Lock this data feed for this camera
+  size_t cam_id_left = message.sensor_ids.at(msg_id_left);
+  size_t cam_id_right = message.sensor_ids.at(msg_id_right);
   std::unique_lock<std::mutex> lck1(mtx_feeds.at(cam_id_left));
   std::unique_lock<std::mutex> lck2(mtx_feeds.at(cam_id_right));
 
-  // Histogram equalize
-  cv::Mat img_left, img_right;
-  cv::equalizeHist(img_leftin, img_left);
-  cv::equalizeHist(img_rightin, img_right);
+  // Histogram equalize images
+  cv::Mat img_left, img_right, mask_left, mask_right;
+  if (histogram_method == HistogramMethod::HISTOGRAM) {
+    cv::equalizeHist(message.images.at(msg_id_left), img_left);
+    cv::equalizeHist(message.images.at(msg_id_right), img_right);
+  } else if (histogram_method == HistogramMethod::CLAHE) {
+    double eq_clip_limit = 10.0;
+    cv::Size eq_win_size = cv::Size(8, 8);
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
+    clahe->apply(message.images.at(msg_id_left), img_left);
+    clahe->apply(message.images.at(msg_id_right), img_right);
+  } else {
+    img_left = message.images.at(msg_id_left);
+    img_right = message.images.at(msg_id_right);
+  }
+  mask_left = message.masks.at(msg_id_left);
+  mask_right = message.masks.at(msg_id_right);
 
   // If we are the first frame (or have lost tracking), initialize our descriptors
   if (pts_last[cam_id_left].empty() || pts_last[cam_id_right].empty()) {
-    perform_detection_stereo(img_left, img_right, pts_last[cam_id_left], pts_last[cam_id_right], desc_last[cam_id_left],
-                             desc_last[cam_id_right], cam_id_left, cam_id_right, ids_last[cam_id_left], ids_last[cam_id_right]);
-    img_last[cam_id_left] = img_left.clone();
-    img_last[cam_id_right] = img_right.clone();
+    perform_detection_stereo(img_left, img_right, mask_left, mask_right, pts_last[cam_id_left], pts_last[cam_id_right],
+                             desc_last[cam_id_left], desc_last[cam_id_right], cam_id_left, cam_id_right, ids_last[cam_id_left],
+                             ids_last[cam_id_right]);
+    img_last[cam_id_left] = img_left;
+    img_last[cam_id_right] = img_right;
+    img_mask_last[cam_id_left] = mask_left;
+    img_mask_last[cam_id_right] = mask_right;
     return;
   }
 
@@ -159,13 +206,10 @@ void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat
   std::vector<size_t> ids_left_new, ids_right_new;
 
   // First, extract new descriptors for this new image
-  perform_detection_stereo(img_left, img_right, pts_left_new, pts_right_new, desc_left_new, desc_right_new, cam_id_left, cam_id_right,
-                           ids_left_new, ids_right_new);
+  perform_detection_stereo(img_left, img_right, mask_left, mask_right, pts_left_new, pts_right_new, desc_left_new, desc_right_new,
+                           cam_id_left, cam_id_right, ids_left_new, ids_right_new);
   rT2 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Our matches temporally
   std::vector<cv::DMatch> matches_ll, matches_rr;
   parallel_for_(cv::Range(0, 2), LambdaBody([&](const cv::Range &range) {
@@ -179,9 +223,6 @@ void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat
                 }));
   rT3 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Get our "good tracks"
   std::vector<cv::KeyPoint> good_left, good_right;
   std::vector<size_t> good_ids_left, good_ids_right;
@@ -246,11 +287,13 @@ void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat
     // Assert that our IDs are the same
     assert(good_ids_left.at(i) == good_ids_right.at(i));
     // Try to undistort the point
-    cv::Point2f npt_l = undistort_point(good_left.at(i).pt, cam_id_left);
-    cv::Point2f npt_r = undistort_point(good_right.at(i).pt, cam_id_right);
+    cv::Point2f npt_l = camera_calib.at(cam_id_left)->undistort_cv(good_left.at(i).pt);
+    cv::Point2f npt_r = camera_calib.at(cam_id_right)->undistort_cv(good_right.at(i).pt);
     // Append to the database
-    database->update_feature(good_ids_left.at(i), timestamp, cam_id_left, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
-    database->update_feature(good_ids_left.at(i), timestamp, cam_id_right, good_right.at(i).pt.x, good_right.at(i).pt.y, npt_r.x, npt_r.y);
+    database->update_feature(good_ids_left.at(i), message.timestamp, cam_id_left, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x,
+                             npt_l.y);
+    database->update_feature(good_ids_left.at(i), message.timestamp, cam_id_right, good_right.at(i).pt.x, good_right.at(i).pt.y, npt_r.x,
+                             npt_r.y);
   }
 
   // Debug info
@@ -258,8 +301,10 @@ void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat
   //       (int)matches_rr.size(),(int)ids_left_new.size(),(int)good_left.size(),num_tracklast);
 
   // Move forward in time
-  img_last[cam_id_left] = img_left.clone();
-  img_last[cam_id_right] = img_right.clone();
+  img_last[cam_id_left] = img_left;
+  img_last[cam_id_right] = img_right;
+  img_mask_last[cam_id_left] = mask_left;
+  img_mask_last[cam_id_right] = mask_right;
   pts_last[cam_id_left] = good_left;
   pts_last[cam_id_right] = good_right;
   ids_last[cam_id_left] = good_ids_left;
@@ -276,38 +321,58 @@ void TrackDescriptor::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat
   // printf("[TIME-DESC]: %.4f seconds for total\n",(rT5-rT1).total_microseconds() * 1e-6);
 }
 
-void TrackDescriptor::perform_detection_monocular(const cv::Mat &img0, std::vector<cv::KeyPoint> &pts0, cv::Mat &desc0,
-                                                  std::vector<size_t> &ids0) {
+void TrackDescriptor::perform_detection_monocular(const cv::Mat &img0, const cv::Mat &mask0, std::vector<cv::KeyPoint> &pts0,
+                                                  cv::Mat &desc0, std::vector<size_t> &ids0) {
 
   // Assert that we need features
   assert(pts0.empty());
 
   // Extract our features (use FAST with griding)
   std::vector<cv::KeyPoint> pts0_ext;
-  Grider_FAST::perform_griding(img0, pts0_ext, num_features, grid_x, grid_y, threshold, true);
+  Grider_FAST::perform_griding(img0, mask0, pts0_ext, num_features, grid_x, grid_y, threshold, true);
 
   // For all new points, extract their descriptors
   cv::Mat desc0_ext;
   this->orb0->compute(img0, pts0_ext, desc0_ext);
 
+  // Create a 2D occupancy grid for this current image
+  // Note that we scale this down, so that each grid point is equal to a set of pixels
+  // This means that we will reject points that less then grid_px_size points away then existing features
+  cv::Size size((int)((float)img0.cols / (float)min_px_dist), (int)((float)img0.rows / (float)min_px_dist));
+  cv::Mat grid_2d = cv::Mat::zeros(size, CV_8UC1);
+
   // For all good matches, lets append to our returned vectors
   // NOTE: if we multi-thread this atomic can cause some randomness due to multiple thread detecting features
   // NOTE: this is due to the fact that we select update features based on feat id
   // NOTE: thus the order will matter since we try to select oldest (smallest id) to update with
   // NOTE: not sure how to remove... maybe a better way?
   for (size_t i = 0; i < pts0_ext.size(); i++) {
-    // Append our keypoints and descriptors
+    // Get current left keypoint, check that it is in bounds
+    cv::KeyPoint kpt = pts0_ext.at(i);
+    int x = (int)kpt.pt.x;
+    int y = (int)kpt.pt.y;
+    int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+    int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+    if (x_grid < 0 || x_grid >= size.width || y_grid < 0 || y_grid >= size.height || x < 0 || x >= img0.cols || y < 0 || y >= img0.rows) {
+      continue;
+    }
+    // Check if this keypoint is near another point
+    if (grid_2d.at<uint8_t>(y_grid, x_grid) > 127)
+      continue;
+    // Else we are good, append our keypoints and descriptors
     pts0.push_back(pts0_ext.at(i));
     desc0.push_back(desc0_ext.row((int)i));
     // Set our IDs to be unique IDs here, will later replace with corrected ones, after temporal matching
     size_t temp = ++currid;
     ids0.push_back(temp);
+    grid_2d.at<uint8_t>(y_grid, x_grid) = 255;
   }
 }
 
-void TrackDescriptor::perform_detection_stereo(const cv::Mat &img0, const cv::Mat &img1, std::vector<cv::KeyPoint> &pts0,
-                                               std::vector<cv::KeyPoint> &pts1, cv::Mat &desc0, cv::Mat &desc1, size_t cam_id0,
-                                               size_t cam_id1, std::vector<size_t> &ids0, std::vector<size_t> &ids1) {
+void TrackDescriptor::perform_detection_stereo(const cv::Mat &img0, const cv::Mat &img1, const cv::Mat &mask0, const cv::Mat &mask1,
+                                               std::vector<cv::KeyPoint> &pts0, std::vector<cv::KeyPoint> &pts1, cv::Mat &desc0,
+                                               cv::Mat &desc1, size_t cam_id0, size_t cam_id1, std::vector<size_t> &ids0,
+                                               std::vector<size_t> &ids1) {
 
   // Assert that we need features
   assert(pts0.empty());
@@ -319,8 +384,8 @@ void TrackDescriptor::perform_detection_stereo(const cv::Mat &img0, const cv::Ma
   parallel_for_(cv::Range(0, 2), LambdaBody([&](const cv::Range &range) {
                   for (int i = range.start; i < range.end; i++) {
                     bool is_left = (i == 0);
-                    Grider_FAST::perform_griding(is_left ? img0 : img1, is_left ? pts0_ext : pts1_ext, num_features, grid_x, grid_y,
-                                                 threshold, true);
+                    Grider_FAST::perform_griding(is_left ? img0 : img1, is_left ? mask0 : mask1, is_left ? pts0_ext : pts1_ext,
+                                                 num_features, grid_x, grid_y, threshold, true);
                     (is_left ? orb0 : orb1)->compute(is_left ? img0 : img1, is_left ? pts0_ext : pts1_ext, is_left ? desc0_ext : desc1_ext);
                   }
                 }));
@@ -329,16 +394,51 @@ void TrackDescriptor::perform_detection_stereo(const cv::Mat &img0, const cv::Ma
   std::vector<cv::DMatch> matches;
   robust_match(pts0_ext, pts1_ext, desc0_ext, desc1_ext, cam_id0, cam_id1, matches);
 
+  // Create a 2D occupancy grid for this current image
+  // Note that we scale this down, so that each grid point is equal to a set of pixels
+  // This means that we will reject points that less then grid_px_size points away then existing features
+  cv::Size size0((int)((float)img0.cols / (float)min_px_dist), (int)((float)img0.rows / (float)min_px_dist));
+  cv::Mat grid_2d_0 = cv::Mat::zeros(size0, CV_8UC1);
+  cv::Size size1((int)((float)img1.cols / (float)min_px_dist), (int)((float)img1.rows / (float)min_px_dist));
+  cv::Mat grid_2d_1 = cv::Mat::zeros(size1, CV_8UC1);
+
   // For all good matches, lets append to our returned vectors
   for (size_t i = 0; i < matches.size(); i++) {
+
     // Get our ids
     int index_pt0 = matches.at(i).queryIdx;
     int index_pt1 = matches.at(i).trainIdx;
+
+    // Get current left/right keypoint, check that it is in bounds
+    cv::KeyPoint kpt0 = pts0_ext.at(index_pt0);
+    cv::KeyPoint kpt1 = pts1_ext.at(index_pt1);
+    int x0 = (int)kpt0.pt.x;
+    int y0 = (int)kpt0.pt.y;
+    int x0_grid = (int)(kpt0.pt.x / (float)min_px_dist);
+    int y0_grid = (int)(kpt0.pt.y / (float)min_px_dist);
+    if (x0_grid < 0 || x0_grid >= size0.width || y0_grid < 0 || y0_grid >= size0.height || x0 < 0 || x0 >= img0.cols || y0 < 0 ||
+        y0 >= img0.rows) {
+      continue;
+    }
+    int x1 = (int)kpt1.pt.x;
+    int y1 = (int)kpt1.pt.y;
+    int x1_grid = (int)(kpt1.pt.x / (float)min_px_dist);
+    int y1_grid = (int)(kpt1.pt.y / (float)min_px_dist);
+    if (x1_grid < 0 || x1_grid >= size1.width || y1_grid < 0 || y1_grid >= size1.height || x1 < 0 || x1 >= img0.cols || y1 < 0 ||
+        y1 >= img0.rows) {
+      continue;
+    }
+
+    // Check if this keypoint is near another point
+    if (grid_2d_0.at<uint8_t>(y0_grid, x0_grid) > 127 || grid_2d_1.at<uint8_t>(y1_grid, x1_grid) > 127)
+      continue;
+
     // Append our keypoints and descriptors
     pts0.push_back(pts0_ext[index_pt0]);
     pts1.push_back(pts1_ext[index_pt1]);
     desc0.push_back(desc0_ext.row(index_pt0));
     desc1.push_back(desc1_ext.row(index_pt1));
+
     // Set our IDs to be unique IDs here, will later replace with corrected ones, after temporal matching
     size_t temp = ++currid;
     ids0.push_back(temp);
@@ -383,14 +483,14 @@ void TrackDescriptor::robust_match(std::vector<cv::KeyPoint> &pts0, std::vector<
   // We don't want to do ransac on distorted image uvs since the mapping is nonlinear
   std::vector<cv::Point2f> pts0_n, pts1_n;
   for (size_t i = 0; i < pts0_rsc.size(); i++) {
-    pts0_n.push_back(undistort_point(pts0_rsc.at(i), id0));
-    pts1_n.push_back(undistort_point(pts1_rsc.at(i), id1));
+    pts0_n.push_back(camera_calib.at(id0)->undistort_cv(pts0_rsc.at(i)));
+    pts1_n.push_back(camera_calib.at(id1)->undistort_cv(pts1_rsc.at(i)));
   }
 
   // Do RANSAC outlier rejection (note since we normalized the max pixel error is now in the normalized cords)
   std::vector<uchar> mask_rsc;
-  double max_focallength_img0 = std::max(camera_k_OPENCV.at(id0)(0, 0), camera_k_OPENCV.at(id0)(1, 1));
-  double max_focallength_img1 = std::max(camera_k_OPENCV.at(id1)(0, 0), camera_k_OPENCV.at(id1)(1, 1));
+  double max_focallength_img0 = std::max(camera_calib.at(id0)->get_K()(0, 0), camera_calib.at(id0)->get_K()(1, 1));
+  double max_focallength_img1 = std::max(camera_calib.at(id1)->get_K()(0, 0), camera_calib.at(id1)->get_K()(1, 1));
   double max_focallength = std::max(max_focallength_img0, max_focallength_img1);
   cv::findFundamentalMat(pts0_n, pts1_n, cv::FM_RANSAC, 1 / max_focallength, 0.999, mask_rsc);
 
@@ -405,43 +505,37 @@ void TrackDescriptor::robust_match(std::vector<cv::KeyPoint> &pts0, std::vector<
 }
 
 void TrackDescriptor::robust_ratio_test(std::vector<std::vector<cv::DMatch>> &matches) {
-
   // Loop through all matches
-  for (auto matchIterator = matches.begin(); matchIterator != matches.end(); ++matchIterator) {
+  for (auto &match : matches) {
     // If 2 NN has been identified, else remove this feature
-    if (matchIterator->size() > 1) {
+    if (match.size() > 1) {
       // check distance ratio, remove it if the ratio is larger
-      if ((*matchIterator)[0].distance / (*matchIterator)[1].distance > knn_ratio) {
-        matchIterator->clear();
+      if (match[0].distance / match[1].distance > knn_ratio) {
+        match.clear();
       }
     } else {
       // does not have 2 neighbours, so remove it
-      matchIterator->clear();
+      match.clear();
     }
   }
 }
 
 void TrackDescriptor::robust_symmetry_test(std::vector<std::vector<cv::DMatch>> &matches1, std::vector<std::vector<cv::DMatch>> &matches2,
                                            std::vector<cv::DMatch> &good_matches) {
-
   // for all matches image 1 -> image 2
-  for (auto matchIterator1 = matches1.begin(); matchIterator1 != matches1.end(); ++matchIterator1) {
-
+  for (auto &match1 : matches1) {
     // ignore deleted matches
-    if (matchIterator1->empty() || matchIterator1->size() < 2)
+    if (match1.empty() || match1.size() < 2)
       continue;
-
     // for all matches image 2 -> image 1
-    for (auto matchIterator2 = matches2.begin(); matchIterator2 != matches2.end(); ++matchIterator2) {
+    for (auto &match2 : matches2) {
       // ignore deleted matches
-      if (matchIterator2->empty() || matchIterator2->size() < 2)
+      if (match2.empty() || match2.size() < 2)
         continue;
-
       // Match symmetry test
-      if ((*matchIterator1)[0].queryIdx == (*matchIterator2)[0].trainIdx &&
-          (*matchIterator2)[0].queryIdx == (*matchIterator1)[0].trainIdx) {
+      if (match1[0].queryIdx == match2[0].trainIdx && match2[0].queryIdx == match1[0].trainIdx) {
         // add symmetrical match
-        good_matches.emplace_back(cv::DMatch((*matchIterator1)[0].queryIdx, (*matchIterator1)[0].trainIdx, (*matchIterator1)[0].distance));
+        good_matches.emplace_back(cv::DMatch(match1[0].queryIdx, match1[0].trainIdx, match1[0].distance));
         // next match in image 1 -> image 2
         break;
       }
diff --git a/ov_core/src/track/TrackDescriptor.h b/ov_core/src/track/TrackDescriptor.h
index e16304cc0..8b40bb541 100644
--- a/ov_core/src/track/TrackDescriptor.h
+++ b/ov_core/src/track/TrackDescriptor.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_TRACK_DESC_H
 #define OV_CORE_TRACK_DESC_H
 
@@ -40,45 +39,50 @@ namespace ov_core {
 class TrackDescriptor : public TrackBase {
 
 public:
-  /**
-   * @brief Public default constructor
-   */
-  TrackDescriptor() : TrackBase(), threshold(10), grid_x(8), grid_y(5), knn_ratio(0.75) {}
-
   /**
    * @brief Public constructor with configuration variables
+   * @param cameras camera calibration object which has all camera intrinsics in it
    * @param numfeats number of features we want want to track (i.e. track 200 points from frame to frame)
    * @param numaruco the max id of the arucotags, so we ensure that we start our non-auroc features above this value
+   * @param binocular if we should do binocular feature tracking or stereo if there are multiple cameras
+   * @param histmethod what type of histogram pre-processing should be done (histogram eq?)
    * @param fast_threshold FAST detection threshold
    * @param gridx size of grid in the x-direction / u-direction
    * @param gridy size of grid in the y-direction / v-direction
+   * @param minpxdist features need to be at least this number pixels away from each other
    * @param knnratio matching ratio needed (smaller value forces top two descriptors during match to be more different)
    */
-  explicit TrackDescriptor(int numfeats, int numaruco, int fast_threshold, int gridx, int gridy, double knnratio)
-      : TrackBase(numfeats, numaruco), threshold(fast_threshold), grid_x(gridx), grid_y(gridy), knn_ratio(knnratio) {}
+  explicit TrackDescriptor(std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras, int numfeats, int numaruco, bool binocular,
+                           HistogramMethod histmethod, int fast_threshold, int gridx, int gridy, int minpxdist, double knnratio)
+      : TrackBase(cameras, numfeats, numaruco, binocular, histmethod), threshold(fast_threshold), grid_x(gridx), grid_y(gridy),
+        min_px_dist(minpxdist), knn_ratio(knnratio) {}
+
+  /**
+   * @brief Process a new image
+   * @param message Contains our timestamp, images, and camera ids
+   */
+  void feed_new_camera(const CameraData &message);
 
+protected:
   /**
    * @brief Process a new monocular image
-   * @param timestamp timestamp the new image occurred at
-   * @param img new cv:Mat grayscale image
-   * @param cam_id the camera id that this new image corresponds too
+   * @param message Contains our timestamp, images, and camera ids
+   * @param msg_id the camera index in message data vector
    */
-  void feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) override;
+  void feed_monocular(const CameraData &message, size_t msg_id);
 
   /**
    * @brief Process new stereo pair of images
-   * @param timestamp timestamp this pair occured at (stereo is synchronised)
-   * @param img_left first grayscaled image
-   * @param img_right second grayscaled image
-   * @param cam_id_left first image camera id
-   * @param cam_id_right second image camera id
+   * @param message Contains our timestamp, images, and camera ids
+   * @param msg_id_left first image index in message data vector
+   * @param msg_id_right second image index in message data vector
    */
-  void feed_stereo(double timestamp, cv::Mat &img_left, cv::Mat &img_right, size_t cam_id_left, size_t cam_id_right) override;
+  void feed_stereo(const CameraData &message, size_t msg_id_left, size_t msg_id_right);
 
-protected:
   /**
    * @brief Detects new features in the current image
    * @param img0 image we will detect features on
+   * @param mask0 mask which has what ROI we do not want features in
    * @param pts0 vector of extracted keypoints
    * @param desc0 vector of the extracted descriptors
    * @param ids0 vector of all new IDs
@@ -88,12 +92,15 @@ class TrackDescriptor : public TrackBase {
    * Our vector of IDs will be later overwritten when we match features temporally to the previous frame's features.
    * See robust_match() for the matching.
    */
-  void perform_detection_monocular(const cv::Mat &img0, std::vector<cv::KeyPoint> &pts0, cv::Mat &desc0, std::vector<size_t> &ids0);
+  void perform_detection_monocular(const cv::Mat &img0, const cv::Mat &mask0, std::vector<cv::KeyPoint> &pts0, cv::Mat &desc0,
+                                   std::vector<size_t> &ids0);
 
   /**
    * @brief Detects new features in the current stereo pair
    * @param img0 left image we will detect features on
    * @param img1 right image we will detect features on
+   * @param mask0 mask which has what ROI we do not want features in
+   * @param mask1 mask which has what ROI we do not want features in
    * @param pts0 left vector of new keypoints
    * @param pts1 right vector of new keypoints
    * @param desc0 left vector of extracted descriptors
@@ -108,9 +115,9 @@ class TrackDescriptor : public TrackBase {
    * Our vector of IDs will be later overwritten when we match features temporally to the previous frame's features.
    * See robust_match() for the matching.
    */
-  void perform_detection_stereo(const cv::Mat &img0, const cv::Mat &img1, std::vector<cv::KeyPoint> &pts0, std::vector<cv::KeyPoint> &pts1,
-                                cv::Mat &desc0, cv::Mat &desc1, size_t cam_id0, size_t cam_id1, std::vector<size_t> &ids0,
-                                std::vector<size_t> &ids1);
+  void perform_detection_stereo(const cv::Mat &img0, const cv::Mat &img1, const cv::Mat &mask0, const cv::Mat &mask1,
+                                std::vector<cv::KeyPoint> &pts0, std::vector<cv::KeyPoint> &pts1, cv::Mat &desc0, cv::Mat &desc1,
+                                size_t cam_id0, size_t cam_id1, std::vector<size_t> &ids0, std::vector<size_t> &ids1);
 
   /**
    * @brief Find matches between two keypoint+descriptor sets.
@@ -152,6 +159,9 @@ class TrackDescriptor : public TrackBase {
   int grid_x;
   int grid_y;
 
+  // Minimum pixel distance to be "far away enough" to be a different extracted feature
+  int min_px_dist;
+
   // The ratio between two kNN matches, if that ratio is larger then this threshold
   // then the two features are too close, so should be considered ambiguous/bad match
   double knn_ratio;
diff --git a/ov_core/src/track/TrackKLT.cpp b/ov_core/src/track/TrackKLT.cpp
index 2a61b872c..a262015c9 100644
--- a/ov_core/src/track/TrackKLT.cpp
+++ b/ov_core/src/track/TrackKLT.cpp
@@ -19,23 +19,62 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "TrackKLT.h"
 
 using namespace ov_core;
 
-void TrackKLT::feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) {
+void TrackKLT::feed_new_camera(const CameraData &message) {
+
+  // Error check that we have all the data
+  if (message.sensor_ids.empty() || message.sensor_ids.size() != message.images.size() || message.images.size() != message.masks.size()) {
+    printf(RED "[ERROR]: MESSAGE DATA SIZES DO NOT MATCH OR EMPTY!!!\n" RESET);
+    printf(RED "[ERROR]:   - message.sensor_ids.size() = %zu\n" RESET, message.sensor_ids.size());
+    printf(RED "[ERROR]:   - message.images.size() = %zu\n" RESET, message.images.size());
+    printf(RED "[ERROR]:   - message.masks.size() = %zu\n" RESET, message.masks.size());
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Either call our stereo or monocular version
+  // If we are doing binocular tracking, then we should parallize our tracking
+  size_t num_images = message.images.size();
+  if (num_images == 1) {
+    feed_monocular(message, 0);
+  } else if (num_images == 2 && use_stereo) {
+    feed_stereo(message, 0, 1);
+  } else if (!use_stereo) {
+    parallel_for_(cv::Range(0, (int)num_images), LambdaBody([&](const cv::Range &range) {
+                    for (int i = range.start; i < range.end; i++) {
+                      feed_monocular(message, i);
+                    }
+                  }));
+  } else {
+    printf(RED "[ERROR]: invalid number of images passed %zu, we only support mono or stereo tracking", num_images);
+    std::exit(EXIT_FAILURE);
+  }
+}
+
+void TrackKLT::feed_monocular(const CameraData &message, size_t msg_id) {
 
   // Start timing
   rT1 = boost::posix_time::microsec_clock::local_time();
 
   // Lock this data feed for this camera
+  size_t cam_id = message.sensor_ids.at(msg_id);
   std::unique_lock<std::mutex> lck(mtx_feeds.at(cam_id));
 
   // Histogram equalize
-  cv::equalizeHist(img, img);
-  // cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
-  // clahe->apply(img, img);
+  cv::Mat img, mask;
+  if (histogram_method == HistogramMethod::HISTOGRAM) {
+    cv::equalizeHist(message.images.at(msg_id), img);
+  } else if (histogram_method == HistogramMethod::CLAHE) {
+    double eq_clip_limit = 10.0;
+    cv::Size eq_win_size = cv::Size(8, 8);
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
+    clahe->apply(message.images.at(msg_id), img);
+  } else {
+    img = message.images.at(msg_id);
+  }
+  mask = message.masks.at(msg_id);
 
   // Extract the new image pyramid
   std::vector<cv::Mat> imgpyr;
@@ -46,40 +85,33 @@ void TrackKLT::feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) {
   // This also handles, the tracking initalization on the first call to this extractor
   if (pts_last[cam_id].empty()) {
     // Detect new features
-    perform_detection_monocular(imgpyr, pts_last[cam_id], ids_last[cam_id]);
+    perform_detection_monocular(imgpyr, mask, pts_last[cam_id], ids_last[cam_id]);
     // Save the current image and pyramid
-    img_last[cam_id] = img.clone();
+    img_last[cam_id] = img;
     img_pyramid_last[cam_id] = imgpyr;
+    img_mask_last[cam_id] = mask;
     return;
   }
 
   // First we should make that the last images have enough features so we can do KLT
   // This will "top-off" our number of tracks so always have a constant number
-  perform_detection_monocular(img_pyramid_last[cam_id], pts_last[cam_id], ids_last[cam_id]);
+  perform_detection_monocular(img_pyramid_last[cam_id], img_mask_last[cam_id], pts_last[cam_id], ids_last[cam_id]);
   rT3 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
-  // Debug
-  // printf("current points = %d,%d\n",(int)pts_left_last.size(),(int)pts_right_last.size());
-
   // Our return success masks, and predicted new features
   std::vector<uchar> mask_ll;
   std::vector<cv::KeyPoint> pts_left_new = pts_last[cam_id];
 
   // Lets track temporally
   perform_matching(img_pyramid_last[cam_id], imgpyr, pts_last[cam_id], pts_left_new, cam_id, cam_id, mask_ll);
-  assert(pts_left_new.size()==ids_last[cam_id].size());
+  assert(pts_left_new.size() == ids_last[cam_id].size());
   rT4 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // If any of our mask is empty, that means we didn't have enough to do ransac, so just return
   if (mask_ll.empty()) {
-    img_last[cam_id] = img.clone();
+    img_last[cam_id] = img;
     img_pyramid_last[cam_id] = imgpyr;
+    img_mask_last[cam_id] = mask;
     pts_last[cam_id].clear();
     ids_last[cam_id].clear();
     printf(RED "[KLT-EXTRACTOR]: Failed to get enough points to do RANSAC, resetting.....\n" RESET);
@@ -93,8 +125,12 @@ void TrackKLT::feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) {
   // Loop through all left points
   for (size_t i = 0; i < pts_left_new.size(); i++) {
     // Ensure we do not have any bad KLT tracks (i.e., points are negative)
-    if (pts_left_new.at(i).pt.x < 0 || pts_left_new.at(i).pt.y < 0 || (int)pts_left_new.at(i).pt.x > img.cols ||
-        (int)pts_left_new.at(i).pt.y > img.rows)
+    if (pts_left_new.at(i).pt.x < 0 || pts_left_new.at(i).pt.y < 0 || (int)pts_left_new.at(i).pt.x >= img.cols ||
+        (int)pts_left_new.at(i).pt.y >= img.rows)
+      continue;
+    // Check if it is in the mask
+    // NOTE: mask has max value of 255 (white) if it should be
+    if ((int)message.masks.at(msg_id).at<uint8_t>((int)pts_left_new.at(i).pt.y, (int)pts_left_new.at(i).pt.x) > 127)
       continue;
     // If it is a good track, and also tracked from left to right
     if (mask_ll[i]) {
@@ -103,18 +139,16 @@ void TrackKLT::feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) {
     }
   }
 
-  //===================================================================================
-  //===================================================================================
-
   // Update our feature database, with theses new observations
   for (size_t i = 0; i < good_left.size(); i++) {
-    cv::Point2f npt_l = undistort_point(good_left.at(i).pt, cam_id);
-    database->update_feature(good_ids_left.at(i), timestamp, cam_id, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
+    cv::Point2f npt_l = camera_calib.at(cam_id)->undistort_cv(good_left.at(i).pt);
+    database->update_feature(good_ids_left.at(i), message.timestamp, cam_id, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
   }
 
   // Move forward in time
-  img_last[cam_id] = img.clone();
+  img_last[cam_id] = img;
   img_pyramid_last[cam_id] = imgpyr;
+  img_mask_last[cam_id] = mask;
   pts_last[cam_id] = good_left;
   ids_last[cam_id] = good_ids_left;
   rT5 = boost::posix_time::microsec_clock::local_time();
@@ -127,27 +161,40 @@ void TrackKLT::feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) {
   // printf("[TIME-KLT]: %.4f seconds for total\n",(rT5-rT1).total_microseconds() * 1e-6);
 }
 
-void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_rightin, size_t cam_id_left, size_t cam_id_right) {
+void TrackKLT::feed_stereo(const CameraData &message, size_t msg_id_left, size_t msg_id_right) {
 
   // Start timing
   rT1 = boost::posix_time::microsec_clock::local_time();
 
   // Lock this data feed for this camera
+  size_t cam_id_left = message.sensor_ids.at(msg_id_left);
+  size_t cam_id_right = message.sensor_ids.at(msg_id_right);
   std::unique_lock<std::mutex> lck1(mtx_feeds.at(cam_id_left));
   std::unique_lock<std::mutex> lck2(mtx_feeds.at(cam_id_right));
 
-  // Histogram equalize and then
-  // Extract image pyramids (boost seems to require us to put all the arguments even if there are defaults....)
-  cv::Mat img_left, img_right;
+  // Histogram equalize images
+  cv::Mat img_left, img_right, mask_left, mask_right;
+  if (histogram_method == HistogramMethod::HISTOGRAM) {
+    cv::equalizeHist(message.images.at(msg_id_left), img_left);
+    cv::equalizeHist(message.images.at(msg_id_right), img_right);
+  } else if (histogram_method == HistogramMethod::CLAHE) {
+    double eq_clip_limit = 10.0;
+    cv::Size eq_win_size = cv::Size(8, 8);
+    cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
+    clahe->apply(message.images.at(msg_id_left), img_left);
+    clahe->apply(message.images.at(msg_id_right), img_right);
+  } else {
+    img_left = message.images.at(msg_id_left);
+    img_right = message.images.at(msg_id_right);
+  }
+  mask_left = message.masks.at(msg_id_left);
+  mask_right = message.masks.at(msg_id_right);
+
+  // Extract image pyramids
   std::vector<cv::Mat> imgpyr_left, imgpyr_right;
-  // cv::Ptr<cv::CLAHE> clahe = cv::createCLAHE(eq_clip_limit, eq_win_size);
   parallel_for_(cv::Range(0, 2), LambdaBody([&](const cv::Range &range) {
                   for (int i = range.start; i < range.end; i++) {
                     bool is_left = (i == 0);
-                    // Histogram equalize
-                    cv::equalizeHist(is_left ? img_leftin : img_rightin, is_left ? img_left : img_right);
-                    // clahe->apply((is_left ? img_leftin : img_rightin), (is_left ? img_left : img_right));
-                    // Extract image pyramids (boost seems to require us to put all the arguments even if there are defaults....)
                     cv::buildOpticalFlowPyramid(is_left ? img_left : img_right, is_left ? imgpyr_left : imgpyr_right, win_size, pyr_levels);
                   }
                 }));
@@ -155,27 +202,27 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
 
   // If we didn't have any successful tracks last time, just extract this time
   // This also handles, the tracking initalization on the first call to this extractor
-  if (pts_last[cam_id_left].empty() || pts_last[cam_id_right].empty()) {
+  if (pts_last[cam_id_left].empty() && pts_last[cam_id_right].empty()) {
     // Track into the new image
-    perform_detection_stereo(imgpyr_left, imgpyr_right, pts_last[cam_id_left], pts_last[cam_id_right], ids_last[cam_id_left],
-                             ids_last[cam_id_right]);
+    perform_detection_stereo(imgpyr_left, imgpyr_right, mask_left, mask_right, cam_id_left, cam_id_right, pts_last[cam_id_left],
+                             pts_last[cam_id_right], ids_last[cam_id_left], ids_last[cam_id_right]);
     // Save the current image and pyramid
     img_last[cam_id_left] = img_left;
     img_last[cam_id_right] = img_right;
     img_pyramid_last[cam_id_left] = imgpyr_left;
     img_pyramid_last[cam_id_right] = imgpyr_right;
+    img_mask_last[cam_id_left] = mask_left;
+    img_mask_last[cam_id_right] = mask_right;
     return;
   }
 
   // First we should make that the last images have enough features so we can do KLT
   // This will "top-off" our number of tracks so always have a constant number
-  perform_detection_stereo(img_pyramid_last[cam_id_left], img_pyramid_last[cam_id_right], pts_last[cam_id_left], pts_last[cam_id_right],
+  perform_detection_stereo(img_pyramid_last[cam_id_left], img_pyramid_last[cam_id_right], img_mask_last[cam_id_left],
+                           img_mask_last[cam_id_right], cam_id_left, cam_id_right, pts_last[cam_id_left], pts_last[cam_id_right],
                            ids_last[cam_id_left], ids_last[cam_id_right]);
   rT3 = boost::posix_time::microsec_clock::local_time();
 
-  //===================================================================================
-  //===================================================================================
-
   // Our return success masks, and predicted new features
   std::vector<uchar> mask_ll, mask_rr;
   std::vector<cv::KeyPoint> pts_left_new = pts_last[cam_id_left];
@@ -207,16 +254,18 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
   //===================================================================================
 
   // If any of our masks are empty, that means we didn't have enough to do ransac, so just return
-  if (mask_ll.empty() || mask_rr.empty()) {
-    img_last[cam_id_left] = std::move(img_left);
-    img_last[cam_id_right] = std::move(img_right);
-    img_pyramid_last[cam_id_left] = std::move(imgpyr_left);
-    img_pyramid_last[cam_id_right] = std::move(imgpyr_right);
+  if (mask_ll.empty() && mask_rr.empty()) {
+    img_last[cam_id_left] = img_left;
+    img_last[cam_id_right] = img_right;
+    img_pyramid_last[cam_id_left] = imgpyr_left;
+    img_pyramid_last[cam_id_right] = imgpyr_right;
+    img_mask_last[cam_id_left] = mask_left;
+    img_mask_last[cam_id_right] = mask_right;
     pts_last[cam_id_left].clear();
     pts_last[cam_id_right].clear();
     ids_last[cam_id_left].clear();
     ids_last[cam_id_right].clear();
-    printf(RED "[KLT-EXTRACTOR]: Failed to get enough points to do RANSAC, resetting....." RESET);
+    printf(RED "[KLT-EXTRACTOR]: Failed to get enough points to do RANSAC, resetting.....\n" RESET);
     return;
   }
 
@@ -245,7 +294,7 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
     if (mask_ll[i] && found_right && mask_rr[index_right]) {
       // Ensure we do not have any bad KLT tracks (i.e., points are negative)
       if (pts_right_new.at(index_right).pt.x < 0 || pts_right_new.at(index_right).pt.y < 0 ||
-          (int)pts_right_new.at(index_right).pt.x > img_right.cols || (int)pts_right_new.at(index_right).pt.y > img_right.rows)
+          (int)pts_right_new.at(index_right).pt.x >= img_right.cols || (int)pts_right_new.at(index_right).pt.y >= img_right.rows)
         continue;
       good_left.push_back(pts_left_new.at(i));
       good_right.push_back(pts_right_new.at(index_right));
@@ -262,8 +311,8 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
   // Loop through all right points
   for (size_t i = 0; i < pts_right_new.size(); i++) {
     // Ensure we do not have any bad KLT tracks (i.e., points are negative)
-    if (pts_right_new.at(i).pt.x < 0 || pts_right_new.at(i).pt.y < 0 || (int)pts_right_new.at(i).pt.x > img_right.cols ||
-        (int)pts_right_new.at(i).pt.y > img_right.rows)
+    if (pts_right_new.at(i).pt.x < 0 || pts_right_new.at(i).pt.y < 0 || (int)pts_right_new.at(i).pt.x >= img_right.cols ||
+        (int)pts_right_new.at(i).pt.y >= img_right.rows)
       continue;
     // See if we have the same feature in the right
     bool added_already = (std::find(good_ids_right.begin(), good_ids_right.end(), ids_last[cam_id_right].at(i)) != good_ids_right.end());
@@ -275,28 +324,29 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
     }
   }
 
-  //===================================================================================
-  //===================================================================================
-
   // Update our feature database, with theses new observations
   for (size_t i = 0; i < good_left.size(); i++) {
-    cv::Point2f npt_l = undistort_point(good_left.at(i).pt, cam_id_left);
-    database->update_feature(good_ids_left.at(i), timestamp, cam_id_left, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x, npt_l.y);
+    cv::Point2f npt_l = camera_calib.at(cam_id_left)->undistort_cv(good_left.at(i).pt);
+    database->update_feature(good_ids_left.at(i), message.timestamp, cam_id_left, good_left.at(i).pt.x, good_left.at(i).pt.y, npt_l.x,
+                             npt_l.y);
   }
   for (size_t i = 0; i < good_right.size(); i++) {
-    cv::Point2f npt_r = undistort_point(good_right.at(i).pt, cam_id_right);
-    database->update_feature(good_ids_right.at(i), timestamp, cam_id_right, good_right.at(i).pt.x, good_right.at(i).pt.y, npt_r.x, npt_r.y);
+    cv::Point2f npt_r = camera_calib.at(cam_id_right)->undistort_cv(good_right.at(i).pt);
+    database->update_feature(good_ids_right.at(i), message.timestamp, cam_id_right, good_right.at(i).pt.x, good_right.at(i).pt.y, npt_r.x,
+                             npt_r.y);
   }
 
   // Move forward in time
-  img_last[cam_id_left] = std::move(img_left);
-  img_last[cam_id_right] = std::move(img_right);
-  img_pyramid_last[cam_id_left] = std::move(imgpyr_left);
-  img_pyramid_last[cam_id_right] = std::move(imgpyr_right);
-  pts_last[cam_id_left] = std::move(good_left);
-  pts_last[cam_id_right] = std::move(good_right);
-  ids_last[cam_id_left] = std::move(good_ids_left);
-  ids_last[cam_id_right] = std::move(good_ids_right);
+  img_last[cam_id_left] = img_left;
+  img_last[cam_id_right] = img_right;
+  img_pyramid_last[cam_id_left] = imgpyr_left;
+  img_pyramid_last[cam_id_right] = imgpyr_right;
+  img_mask_last[cam_id_left] = mask_left;
+  img_mask_last[cam_id_right] = mask_right;
+  pts_last[cam_id_left] = good_left;
+  pts_last[cam_id_right] = good_right;
+  ids_last[cam_id_left] = good_ids_left;
+  ids_last[cam_id_right] = good_ids_right;
   rT6 = boost::posix_time::microsec_clock::local_time();
 
   // Timing information
@@ -308,60 +358,75 @@ void TrackKLT::feed_stereo(double timestamp, cv::Mat &img_leftin, cv::Mat &img_r
   // printf("[TIME-KLT]: %.4f seconds for total\n",(rT6-rT1).total_microseconds() * 1e-6);
 }
 
-void TrackKLT::perform_detection_monocular(const std::vector<cv::Mat> &img0pyr, std::vector<cv::KeyPoint> &pts0,
+void TrackKLT::perform_detection_monocular(const std::vector<cv::Mat> &img0pyr, const cv::Mat &mask0, std::vector<cv::KeyPoint> &pts0,
                                            std::vector<size_t> &ids0) {
 
-  // First compute how many more features we need to extract from this image
-  int num_featsneeded = num_features - (int)pts0.size();
-
-  // If we don't need any features, just return
-  if (num_featsneeded < 0.2 * num_features)
-    return;
-
   // Create a 2D occupancy grid for this current image
   // Note that we scale this down, so that each grid point is equal to a set of pixels
   // This means that we will reject points that less then grid_px_size points away then existing features
-  // TODO: figure out why I need to add the windowsize of the klt to handle features that are outside the image bound
-  // TODO: I assume this is because klt of features at the corners is not really well defined, thus if it doesn't get a match it will be
-  // out-of-bounds
-  Eigen::MatrixXi grid_2d =
-      Eigen::MatrixXi::Zero((int)(img0pyr.at(0).rows / min_px_dist) + 15, (int)(img0pyr.at(0).cols / min_px_dist) + 15);
+  cv::Size size((int)((float)img0pyr.at(0).cols / (float)min_px_dist), (int)((float)img0pyr.at(0).rows / (float)min_px_dist));
+  cv::Mat grid_2d = cv::Mat::zeros(size, CV_8UC1);
   auto it0 = pts0.begin();
-  auto it2 = ids0.begin();
+  auto it1 = ids0.begin();
   while (it0 != pts0.end()) {
-    // Get current left keypoint
+    // Get current left keypoint, check that it is in bounds
     cv::KeyPoint kpt = *it0;
+    int x = (int)kpt.pt.x;
+    int y = (int)kpt.pt.y;
+    int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+    int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+    if (x_grid < 0 || x_grid >= size.width || y_grid < 0 || y_grid >= size.height || x < 0 || x >= img0pyr.at(0).cols || y < 0 ||
+        y >= img0pyr.at(0).rows) {
+      it0 = pts0.erase(it0);
+      it1 = ids0.erase(it1);
+      continue;
+    }
     // Check if this keypoint is near another point
-    if (grid_2d((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1) {
+    if (grid_2d.at<uint8_t>(y_grid, x_grid) > 127) {
       it0 = pts0.erase(it0);
-      it2 = ids0.erase(it2);
+      it1 = ids0.erase(it1);
+      continue;
+    }
+    // Now check if it is in a mask area or not
+    // NOTE: mask has max value of 255 (white) if it should be
+    if (mask0.at<uint8_t>(y, x) > 127) {
+      it0 = pts0.erase(it0);
+      it1 = ids0.erase(it1);
       continue;
     }
     // Else we are good, move forward to the next point
-    grid_2d((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
+    grid_2d.at<uint8_t>(y_grid, x_grid) = 255;
     it0++;
-    it2++;
+    it1++;
   }
 
+  // First compute how many more features we need to extract from this image
+  int num_featsneeded = num_features - (int)pts0.size();
+
+  // If we don't need any features, just return
+  if (num_featsneeded < std::min(75, (int)(0.2 * num_features)))
+    return;
+
   // Extract our features (use fast with griding)
   std::vector<cv::KeyPoint> pts0_ext;
-  Grider_FAST::perform_griding(img0pyr.at(0), pts0_ext, num_featsneeded, grid_x, grid_y, threshold, true);
+  Grider_FAST::perform_griding(img0pyr.at(0), mask0, pts0_ext, num_featsneeded, grid_x, grid_y, threshold, true);
 
   // Now, reject features that are close a current feature
   std::vector<cv::KeyPoint> kpts0_new;
   std::vector<cv::Point2f> pts0_new;
   for (auto &kpt : pts0_ext) {
     // Check that it is in bounds
-    bool outof_bounds_0 = (kpt.pt.x < 0 || kpt.pt.y < 0 || kpt.pt.x >= img0pyr.at(0).cols || kpt.pt.y >= img0pyr.at(0).rows);
-    if (outof_bounds_0)
+    int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+    int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+    if (x_grid < 0 || x_grid >= size.width || y_grid < 0 || y_grid >= size.height)
       continue;
     // See if there is a point at this location
-    if (grid_2d((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1)
+    if (grid_2d.at<uint8_t>(y_grid, x_grid) > 127)
       continue;
     // Else lets add it!
     kpts0_new.push_back(kpt);
     pts0_new.push_back(kpt.pt);
-    grid_2d((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
+    grid_2d.at<uint8_t>(y_grid, x_grid) = 255;
   }
 
   // Loop through and record only ones that are valid
@@ -380,49 +445,45 @@ void TrackKLT::perform_detection_monocular(const std::vector<cv::Mat> &img0pyr,
   }
 }
 
-void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, const std::vector<cv::Mat> &img1pyr,
-                                        std::vector<cv::KeyPoint> &pts0, std::vector<cv::KeyPoint> &pts1,
-                                        std::vector<size_t> &ids0, std::vector<size_t> &ids1) {
+void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, const std::vector<cv::Mat> &img1pyr, const cv::Mat &mask0,
+                                        const cv::Mat &mask1, size_t cam_id_left, size_t cam_id_right, std::vector<cv::KeyPoint> &pts0,
+                                        std::vector<cv::KeyPoint> &pts1, std::vector<size_t> &ids0, std::vector<size_t> &ids1) {
 
   // Create a 2D occupancy grid for this current image
   // Note that we scale this down, so that each grid point is equal to a set of pixels
   // This means that we will reject points that less then grid_px_size points away then existing features
-  // TODO: figure out why I need to add the windowsize of the klt to handle features that are outside the image bound
-  // TODO: I assume this is because klt of features at the corners is not really well defined, thus if it doesn't get a match it will be
-  // out-of-bounds
-  Eigen::MatrixXi grid_2d_0 =
-      Eigen::MatrixXi::Zero((int)(img0pyr.at(0).rows / min_px_dist) + 15, (int)(img0pyr.at(0).cols / min_px_dist) + 15);
-  Eigen::MatrixXi grid_2d_1 =
-      Eigen::MatrixXi::Zero((int)(img1pyr.at(0).rows / min_px_dist) + 15, (int)(img1pyr.at(0).cols / min_px_dist) + 15);
+  cv::Size size0((int)((float)img0pyr.at(0).cols / (float)min_px_dist), (int)((float)img0pyr.at(0).rows / (float)min_px_dist));
+  cv::Mat grid_2d_0 = cv::Mat::zeros(size0, CV_8UC1);
   auto it0 = pts0.begin();
   auto it1 = ids0.begin();
   while (it0 != pts0.end()) {
-    // Get current left keypoint
+    // Get current left keypoint, check that it is in bounds
     cv::KeyPoint kpt = *it0;
-    // Check if this keypoint is near another point
-    if (grid_2d_0((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1) {
+    int x = (int)kpt.pt.x;
+    int y = (int)kpt.pt.y;
+    int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+    int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+    if (x_grid < 0 || x_grid >= size0.width || y_grid < 0 || y_grid >= size0.height || x < 0 || x >= img0pyr.at(0).cols || y < 0 ||
+        y >= img0pyr.at(0).rows) {
       it0 = pts0.erase(it0);
       it1 = ids0.erase(it1);
       continue;
     }
-    // Else we are good, move forward to the next point
-    grid_2d_0((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
-    it0++;
-    it1++;
-  }
-  it0 = pts1.begin();
-  it1 = ids1.begin();
-  while (it0 != pts1.end()) {
-    // Get current right keypoint
-    cv::KeyPoint kpt = *it0;
     // Check if this keypoint is near another point
-    if (grid_2d_1((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1) {
-      it0 = pts1.erase(it0);
-      it1 = ids1.erase(it1);
+    if (grid_2d_0.at<uint8_t>(y_grid, x_grid) > 127) {
+      it0 = pts0.erase(it0);
+      it1 = ids0.erase(it1);
+      continue;
+    }
+    // Now check if it is in a mask area or not
+    // NOTE: mask has max value of 255 (white) if it should be
+    if (mask0.at<uint8_t>(y, x) > 127) {
+      it0 = pts0.erase(it0);
+      it1 = ids0.erase(it1);
       continue;
     }
     // Else we are good, move forward to the next point
-    grid_2d_1((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
+    grid_2d_0.at<uint8_t>(y_grid, x_grid) = 255;
     it0++;
     it1++;
   }
@@ -433,39 +494,47 @@ void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, con
   // LEFT: if we need features we should extract them in the current frame
   // LEFT: we will also try to track them from this frame over to the right frame
   // LEFT: in the case that we have two features that are the same, then we should merge them
-  if (num_featsneeded_0 > 0.2 * num_features) {
+  if (num_featsneeded_0 > std::min(75, (int)(0.2 * num_features))) {
 
     // Extract our features (use fast with griding)
     std::vector<cv::KeyPoint> pts0_ext;
-    Grider_FAST::perform_griding(img0pyr.at(0), pts0_ext, num_featsneeded_0, grid_x, grid_y, threshold, true);
+    Grider_FAST::perform_griding(img0pyr.at(0), mask0, pts0_ext, num_featsneeded_0, grid_x, grid_y, threshold, true);
 
     // Now, reject features that are close a current feature
     std::vector<cv::KeyPoint> kpts0_new;
     std::vector<cv::Point2f> pts0_new;
     for (auto &kpt : pts0_ext) {
+      // Check that it is in bounds
+      int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+      int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+      if (x_grid < 0 || x_grid >= size0.width || y_grid < 0 || y_grid >= size0.height)
+        continue;
       // See if there is a point at this location
-      if (grid_2d_0((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1)
+      if (grid_2d_0.at<uint8_t>(y_grid, x_grid) > 127)
         continue;
       // Else lets add it!
+      grid_2d_0.at<uint8_t>(y_grid, x_grid) = 255;
       kpts0_new.push_back(kpt);
       pts0_new.push_back(kpt.pt);
-      grid_2d_0((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
     }
 
     // TODO: Project points from the left frame into the right frame
     // TODO: This will not work for large baseline systems.....
+    // TODO: If we had some depth estimates we could do a better projection
+    // TODO: Or project and search along the epipolar line??
     std::vector<cv::KeyPoint> kpts1_new;
     std::vector<cv::Point2f> pts1_new;
     kpts1_new = kpts0_new;
     pts1_new = pts0_new;
 
-    // If we have points, do KLT tracking to get the valid projections
+    // If we have points, do KLT tracking to get the valid projections into the right image
     if (!pts0_new.empty()) {
 
       // Do our KLT tracking from the left to the right frame of reference
       // Note: we have a pretty big window size here since our projection might be bad
       // Note: but this might cause failure in cases of repeated textures (eg. checkerboard)
       std::vector<uchar> mask;
+      // perform_matching(img0pyr, img1pyr, kpts0_new, kpts1_new, cam_id_left, cam_id_right, mask);
       std::vector<float> error;
       cv::TermCriteria term_crit = cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 10, 0.01);
       cv::calcOpticalFlowPyrLK(img0pyr, img1pyr, pts0_new, pts1_new, mask, error, win_size, pyr_levels, term_crit,
@@ -474,17 +543,22 @@ void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, con
       // Loop through and record only ones that are valid
       for (size_t i = 0; i < pts0_new.size(); i++) {
 
-        // Check that our tracks are in bounds
-        bool outof_bounds_0 = (pts0_new.at(i).x < 0 || pts0_new.at(i).y < 0 || pts0_new.at(i).x >= img0pyr.at(0).cols ||
-                               pts0_new.at(i).y >= img0pyr.at(0).rows);
-        bool outof_bounds_1 = (pts1_new.at(i).x < 0 || pts1_new.at(i).y < 0 || pts1_new.at(i).x >= img1pyr.at(0).cols ||
-                               pts1_new.at(i).y >= img1pyr.at(0).rows);
+        // Check that it is in bounds
+        if ((int)pts0_new.at(i).x < 0 || (int)pts0_new.at(i).x >= img0pyr.at(0).cols || (int)pts0_new.at(i).y < 0 ||
+            (int)pts0_new.at(i).y >= img0pyr.at(0).rows) {
+          continue;
+        }
+        if ((int)pts1_new.at(i).x < 0 || (int)pts1_new.at(i).x >= img1pyr.at(0).cols || (int)pts1_new.at(i).y < 0 ||
+            (int)pts1_new.at(i).y >= img1pyr.at(0).rows) {
+          continue;
+        }
 
-        // If this is not already in the right image, then we should treat it as a stereo
-        // Otherwise we will treat this as just a monocular track of the feature
+        // Check to see if it there is already a feature in the right image at this location
+        //  1) If this is not already in the right image, then we should treat it as a stereo
+        //  2) Otherwise we will treat this as just a monocular track of the feature
         // TODO: we should check to see if we can combine this new feature and the one in the right
-        if (!outof_bounds_0 && mask[i] == 1 && !outof_bounds_1 &&
-            !(grid_2d_1((int)(pts1_new.at(i).y / min_px_dist), (int)(pts1_new.at(i).x / min_px_dist)) == 1)) {
+        // TODO: seems if reject features which overlay with right features already we have very poor tracking perf
+        if (mask[i] == 1) {
           // update the uv coordinates
           kpts0_new.at(i).pt = pts0_new.at(i);
           kpts1_new.at(i).pt = pts1_new.at(i);
@@ -495,7 +569,7 @@ void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, con
           size_t temp = ++currid;
           ids0.push_back(temp);
           ids1.push_back(temp);
-        } else if (!outof_bounds_0) {
+        } else {
           // update the uv coordinates
           kpts0_new.at(i).pt = pts0_new.at(i);
           // append the new uv coordinate
@@ -508,25 +582,73 @@ void TrackKLT::perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, con
     }
   }
 
+  // RIGHT: Now summarise the number of tracks in the right image
+  // RIGHT: We will try to extract some monocular features if we have the room
+  // RIGHT: This will also remove features if there are multiple in the same location
+  cv::Size size1((int)((float)img1pyr.at(0).cols / (float)min_px_dist), (int)((float)img1pyr.at(0).rows / (float)min_px_dist));
+  cv::Mat grid_2d_1 = cv::Mat::zeros(size1, CV_8UC1);
+  it0 = pts1.begin();
+  it1 = ids1.begin();
+  while (it0 != pts1.end()) {
+    // Get current left keypoint, check that it is in bounds
+    cv::KeyPoint kpt = *it0;
+    int x = (int)kpt.pt.x;
+    int y = (int)kpt.pt.y;
+    int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+    int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+    if (x_grid < 0 || x_grid >= size1.width || y_grid < 0 || y_grid >= size1.height || x < 0 || x >= img1pyr.at(0).cols || y < 0 ||
+        y >= img1pyr.at(0).rows) {
+      it0 = pts1.erase(it0);
+      it1 = ids1.erase(it1);
+      continue;
+    }
+    // Check if this is a stereo point
+    bool is_stereo = (std::find(ids0.begin(), ids0.end(), *it1) != ids0.end());
+    // Check if this keypoint is near another point
+    // NOTE: if it is *not* a stereo point, then we will not delete the feature
+    // NOTE: this means we might have a mono and stereo feature near each other, but that is ok
+    if (grid_2d_1.at<uint8_t>(y_grid, x_grid) > 127 && !is_stereo) {
+      it0 = pts1.erase(it0);
+      it1 = ids1.erase(it1);
+      continue;
+    }
+    // Now check if it is in a mask area or not
+    // NOTE: mask has max value of 255 (white) if it should be
+    if (mask1.at<uint8_t>(y, x) > 127) {
+      it0 = pts1.erase(it0);
+      it1 = ids1.erase(it1);
+      continue;
+    }
+    // Else we are good, move forward to the next point
+    grid_2d_1.at<uint8_t>(y_grid, x_grid) = 255;
+    it0++;
+    it1++;
+  }
+
   // RIGHT: if we need features we should extract them in the current frame
   // RIGHT: note that we don't track them to the left as we already did left->right tracking above
   int num_featsneeded_1 = num_features - (int)pts1.size();
-  if (num_featsneeded_1 > 0.2 * num_features) {
+  if (num_featsneeded_1 > std::min(75, (int)(0.2 * num_features))) {
 
     // Extract our features (use fast with griding)
     std::vector<cv::KeyPoint> pts1_ext;
-    Grider_FAST::perform_griding(img1pyr.at(0), pts1_ext, num_featsneeded_1, grid_x, grid_y, threshold, true);
+    Grider_FAST::perform_griding(img1pyr.at(0), mask1, pts1_ext, num_featsneeded_1, grid_x, grid_y, threshold, true);
 
     // Now, reject features that are close a current feature
     for (auto &kpt : pts1_ext) {
+      // Check that it is in bounds
+      int x_grid = (int)(kpt.pt.x / (float)min_px_dist);
+      int y_grid = (int)(kpt.pt.y / (float)min_px_dist);
+      if (x_grid < 0 || x_grid >= size1.width || y_grid < 0 || y_grid >= size1.height)
+        continue;
       // See if there is a point at this location
-      if (grid_2d_1((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) == 1)
+      if (grid_2d_1.at<uint8_t>(y_grid, x_grid) > 127)
         continue;
       // Else lets add it!
       pts1.push_back(kpt);
       size_t temp = ++currid;
       ids1.push_back(temp);
-      grid_2d_1((int)(kpt.pt.y / min_px_dist), (int)(kpt.pt.x / min_px_dist)) = 1;
+      grid_2d_1.at<uint8_t>(y_grid, x_grid) = 255;
     }
   }
 }
@@ -559,21 +681,21 @@ void TrackKLT::perform_matching(const std::vector<cv::Mat> &img0pyr, const std::
   // Now do KLT tracking to get the valid new points
   std::vector<uchar> mask_klt;
   std::vector<float> error;
-  cv::TermCriteria term_crit = cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 10, 0.01);
+  cv::TermCriteria term_crit = cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 20, 0.01);
   cv::calcOpticalFlowPyrLK(img0pyr, img1pyr, pts0, pts1, mask_klt, error, win_size, pyr_levels, term_crit, cv::OPTFLOW_USE_INITIAL_FLOW);
 
   // Normalize these points, so we can then do ransac
   // We don't want to do ransac on distorted image uvs since the mapping is nonlinear
   std::vector<cv::Point2f> pts0_n, pts1_n;
   for (size_t i = 0; i < pts0.size(); i++) {
-    pts0_n.push_back(undistort_point(pts0.at(i), id0));
-    pts1_n.push_back(undistort_point(pts1.at(i), id1));
+    pts0_n.push_back(camera_calib.at(id0)->undistort_cv(pts0.at(i)));
+    pts1_n.push_back(camera_calib.at(id1)->undistort_cv(pts1.at(i)));
   }
 
   // Do RANSAC outlier rejection (note since we normalized the max pixel error is now in the normalized cords)
   std::vector<uchar> mask_rsc;
-  double max_focallength_img0 = std::max(camera_k_OPENCV.at(id0)(0, 0), camera_k_OPENCV.at(id0)(1, 1));
-  double max_focallength_img1 = std::max(camera_k_OPENCV.at(id1)(0, 0), camera_k_OPENCV.at(id1)(1, 1));
+  double max_focallength_img0 = std::max(camera_calib.at(id0)->get_K()(0, 0), camera_calib.at(id0)->get_K()(1, 1));
+  double max_focallength_img1 = std::max(camera_calib.at(id1)->get_K()(0, 0), camera_calib.at(id1)->get_K()(1, 1));
   double max_focallength = std::max(max_focallength_img0, max_focallength_img1);
   cv::findFundamentalMat(pts0_n, pts1_n, cv::FM_RANSAC, 1.0 / max_focallength, 0.999, mask_rsc);
 
diff --git a/ov_core/src/track/TrackKLT.h b/ov_core/src/track/TrackKLT.h
index 9621fbec6..f2810b045 100644
--- a/ov_core/src/track/TrackKLT.h
+++ b/ov_core/src/track/TrackKLT.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_TRACK_KLT_H
 #define OV_CORE_TRACK_KLT_H
 
@@ -34,51 +33,55 @@ namespace ov_core {
  * We can track either monocular cameras across time (temporally) along with
  * stereo cameras which we also track across time (temporally) but track from left to right
  * to find the stereo correspondence information also.
- * This uses the [calcOpticalFlowPyrLK](https://github.com/opencv/opencv/blob/master/modules/video/src/lkpyramid.cpp) OpenCV function to do
- * the KLT tracking.
+ * This uses the [calcOpticalFlowPyrLK](https://github.com/opencv/opencv/blob/master/modules/video/src/lkpyramid.cpp)
+ * OpenCV function to do the KLT tracking.
  */
 class TrackKLT : public TrackBase {
 
 public:
-  /**
-   * @brief Public default constructor
-   */
-  TrackKLT() : TrackBase(), threshold(10), grid_x(8), grid_y(5), min_px_dist(30) {}
-
   /**
    * @brief Public constructor with configuration variables
+   * @param cameras camera calibration object which has all camera intrinsics in it
    * @param numfeats number of features we want want to track (i.e. track 200 points from frame to frame)
    * @param numaruco the max id of the arucotags, so we ensure that we start our non-auroc features above this value
+   * @param binocular if we should do binocular feature tracking or stereo if there are multiple cameras
+   * @param histmethod what type of histogram pre-processing should be done (histogram eq?)
    * @param fast_threshold FAST detection threshold
    * @param gridx size of grid in the x-direction / u-direction
    * @param gridy size of grid in the y-direction / v-direction
    * @param minpxdist features need to be at least this number pixels away from each other
    */
-  explicit TrackKLT(int numfeats, int numaruco, int fast_threshold, int gridx, int gridy, int minpxdist)
-      : TrackBase(numfeats, numaruco), threshold(fast_threshold), grid_x(gridx), grid_y(gridy), min_px_dist(minpxdist) {}
+  explicit TrackKLT(std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras, int numfeats, int numaruco, bool binocular,
+                    HistogramMethod histmethod, int fast_threshold, int gridx, int gridy, int minpxdist)
+      : TrackBase(cameras, numfeats, numaruco, binocular, histmethod), threshold(fast_threshold), grid_x(gridx), grid_y(gridy),
+        min_px_dist(minpxdist) {}
 
+  /**
+   * @brief Process a new image
+   * @param message Contains our timestamp, images, and camera ids
+   */
+  void feed_new_camera(const CameraData &message);
+
+protected:
   /**
    * @brief Process a new monocular image
-   * @param timestamp timestamp the new image occurred at
-   * @param img new cv:Mat grayscale image
-   * @param cam_id the camera id that this new image corresponds too
+   * @param message Contains our timestamp, images, and camera ids
+   * @param msg_id the camera index in message data vector
    */
-  void feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) override;
+  void feed_monocular(const CameraData &message, size_t msg_id);
 
   /**
    * @brief Process new stereo pair of images
-   * @param timestamp timestamp this pair occured at (stereo is synchronised)
-   * @param img_left first grayscaled image
-   * @param img_right second grayscaled image
-   * @param cam_id_left first image camera id
-   * @param cam_id_right second image camera id
+   * @param message Contains our timestamp, images, and camera ids
+   * @param msg_id_left first image index in message data vector
+   * @param msg_id_right second image index in message data vector
    */
-  void feed_stereo(double timestamp, cv::Mat &img_left, cv::Mat &img_right, size_t cam_id_left, size_t cam_id_right) override;
+  void feed_stereo(const CameraData &message, size_t msg_id_left, size_t msg_id_right);
 
-protected:
   /**
    * @brief Detects new features in the current image
    * @param img0pyr image we will detect features on (first level of pyramid)
+   * @param mask0 mask which has what ROI we do not want features in
    * @param pts0 vector of currently extracted keypoints in this image
    * @param ids0 vector of feature ids for each currently extracted keypoint
    *
@@ -86,12 +89,17 @@ class TrackKLT : public TrackBase {
    * Will try to always have the "max_features" being tracked through KLT at each timestep.
    * Passed images should already be grayscaled.
    */
-  void perform_detection_monocular(const std::vector<cv::Mat> &img0pyr, std::vector<cv::KeyPoint> &pts0, std::vector<size_t> &ids0);
+  void perform_detection_monocular(const std::vector<cv::Mat> &img0pyr, const cv::Mat &mask0, std::vector<cv::KeyPoint> &pts0,
+                                   std::vector<size_t> &ids0);
 
   /**
    * @brief Detects new features in the current stereo pair
    * @param img0pyr left image we will detect features on (first level of pyramid)
    * @param img1pyr right image we will detect features on (first level of pyramid)
+   * @param mask0 mask which has what ROI we do not want features in
+   * @param mask1 mask which has what ROI we do not want features in
+   * @param cam_id_left first camera sensor id
+   * @param cam_id_right second camera sensor id
    * @param pts0 left vector of currently extracted keypoints
    * @param pts1 right vector of currently extracted keypoints
    * @param ids0 left vector of feature ids for each currently extracted keypoint
@@ -102,7 +110,8 @@ class TrackKLT : public TrackBase {
    * If we have valid tracks, then we have both the keypoint on the left and its matching point in the right image.
    * Will try to always have the "max_features" being tracked through KLT at each timestep.
    */
-  void perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, const std::vector<cv::Mat> &img1pyr, std::vector<cv::KeyPoint> &pts0,
+  void perform_detection_stereo(const std::vector<cv::Mat> &img0pyr, const std::vector<cv::Mat> &img1pyr, const cv::Mat &mask0,
+                                const cv::Mat &mask1, size_t cam_id_left, size_t cam_id_right, std::vector<cv::KeyPoint> &pts0,
                                 std::vector<cv::KeyPoint> &pts1, std::vector<size_t> &ids0, std::vector<size_t> &ids1);
 
   /**
@@ -122,9 +131,6 @@ class TrackKLT : public TrackBase {
   void perform_matching(const std::vector<cv::Mat> &img0pyr, const std::vector<cv::Mat> &img1pyr, std::vector<cv::KeyPoint> &pts0,
                         std::vector<cv::KeyPoint> &pts1, size_t id0, size_t id1, std::vector<uchar> &mask_out);
 
-  // Timing variables
-  boost::posix_time::ptime rT1, rT2, rT3, rT4, rT5, rT6, rT7;
-
   // Parameters for our FAST grid detector
   int threshold;
   int grid_x;
@@ -133,13 +139,9 @@ class TrackKLT : public TrackBase {
   // Minimum pixel distance to be "far away enough" to be a different extracted feature
   int min_px_dist;
 
-  // How many pyramid levels to track on and the window size to reduce by
+  // How many pyramid levels to track
   int pyr_levels = 3;
-  cv::Size win_size = cv::Size(15, 15);
-
-  // Alternative histagram equalization
-  double eq_clip_limit = 10.0;
-  cv::Size eq_win_size = cv::Size(8, 8);
+  cv::Size win_size = cv::Size(20, 20);
 
   // Last set of image pyramids
   std::map<size_t, std::vector<cv::Mat>> img_pyramid_last;
diff --git a/ov_core/src/track/TrackSIM.cpp b/ov_core/src/track/TrackSIM.cpp
index f22534593..f663746b1 100644
--- a/ov_core/src/track/TrackSIM.cpp
+++ b/ov_core/src/track/TrackSIM.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "TrackSIM.h"
 
 using namespace ov_core;
@@ -56,7 +55,7 @@ void TrackSIM::feed_measurement_simulation(double timestamp, const std::vector<i
       good_ids_left.push_back(id);
 
       // Append to the database
-      cv::Point2f npt_l = undistort_point(kpt.pt, cam_id);
+      cv::Point2f npt_l = camera_calib.at(cam_id)->undistort_cv(kpt.pt);
       database->update_feature(id, timestamp, cam_id, kpt.pt.x, kpt.pt.y, npt_l.x, npt_l.y);
     }
 
@@ -65,6 +64,7 @@ void TrackSIM::feed_measurement_simulation(double timestamp, const std::vector<i
 
     // Move forward in time
     img_last[cam_id] = cv::Mat::zeros(cv::Size(wh.first, wh.second), CV_8UC1);
+    img_mask_last[cam_id] = cv::Mat::zeros(cv::Size(wh.first, wh.second), CV_8UC1);
     pts_last[cam_id] = good_left;
     ids_last[cam_id] = good_ids_left;
   }
diff --git a/ov_core/src/track/TrackSIM.h b/ov_core/src/track/TrackSIM.h
index c2bf0dfbf..9ddd61e06 100644
--- a/ov_core/src/track/TrackSIM.h
+++ b/ov_core/src/track/TrackSIM.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_TRACK_SIM_H
 #define OV_CORE_TRACK_SIM_H
 
@@ -38,26 +37,24 @@ class TrackSIM : public TrackBase {
 public:
   /**
    * @brief Public constructor with configuration variables
+   * @param cameras camera calibration object which has all camera intrinsics in it
    * @param numaruco the max id of the arucotags, so we ensure that we start our non-auroc features above this value
    */
-  TrackSIM(int numaruco) : TrackBase(0, numaruco) {}
-
+  TrackSIM(std::unordered_map<size_t, std::shared_ptr<CamBase>> cameras, int numaruco)
+      : TrackBase(cameras, 0, numaruco, false, HistogramMethod::NONE) {}
   /**
    * @brief Set the width and height for the cameras
    * @param _camera_wh Width and height for each camera
    */
   void set_width_height(std::map<size_t, std::pair<int, int>> _camera_wh) { this->camera_wh = _camera_wh; }
 
-  /// @warning This function should not be used!! Use @ref feed_measurement_simulation() instead.
-  void feed_monocular(double timestamp, cv::Mat &img, size_t cam_id) override {
-    printf(RED "[SIM]: SIM TRACKER FEED MONOCULAR CALLED!!!\n" RESET);
-    printf(RED "[SIM]: THIS SHOULD NEVER HAPPEN!\n" RESET);
-    std::exit(EXIT_FAILURE);
-  }
-
-  /// @warning This function should not be used!! Use @ref feed_measurement_simulation() instead.
-  void feed_stereo(double timestamp, cv::Mat &img_left, cv::Mat &img_right, size_t cam_id_left, size_t cam_id_right) override {
-    printf(RED "[SIM]: SIM TRACKER FEED STEREO CALLED!!!\n" RESET);
+  /**
+   * @brief Process a new image
+   * @warning This function should not be used!! Use @ref feed_measurement_simulation() instead.
+   * @param message Contains our timestamp, images, and camera ids
+   */
+  void feed_new_camera(const CameraData &message) override {
+    printf(RED "[SIM]: SIM TRACKER FEED NEW CAMERA CALLED!!!\n" RESET);
     printf(RED "[SIM]: THIS SHOULD NEVER HAPPEN!\n" RESET);
     std::exit(EXIT_FAILURE);
   }
diff --git a/ov_core/src/types/IMU.h b/ov_core/src/types/IMU.h
index a50cab076..cf1b08105 100644
--- a/ov_core/src/types/IMU.h
+++ b/ov_core/src/types/IMU.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_IMU_H
 #define OV_TYPE_TYPE_IMU_H
 
diff --git a/ov_core/src/types/JPLQuat.h b/ov_core/src/types/JPLQuat.h
index 6080f700f..7a0dc29fe 100644
--- a/ov_core/src/types/JPLQuat.h
+++ b/ov_core/src/types/JPLQuat.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_JPLQUAT_H
 #define OV_TYPE_TYPE_JPLQUAT_H
 
diff --git a/ov_core/src/types/Landmark.cpp b/ov_core/src/types/Landmark.cpp
index 310c85e2d..79613baec 100644
--- a/ov_core/src/types/Landmark.cpp
+++ b/ov_core/src/types/Landmark.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "Landmark.h"
 
 using namespace ov_type;
diff --git a/ov_core/src/types/Landmark.h b/ov_core/src/types/Landmark.h
index 4e99698f0..2f9aa963d 100644
--- a/ov_core/src/types/Landmark.h
+++ b/ov_core/src/types/Landmark.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_LANDMARK_H
 #define OV_TYPE_TYPE_LANDMARK_H
 
diff --git a/ov_core/src/types/LandmarkRepresentation.h b/ov_core/src/types/LandmarkRepresentation.h
index fc7b574e0..24bd22bc4 100644
--- a/ov_core/src/types/LandmarkRepresentation.h
+++ b/ov_core/src/types/LandmarkRepresentation.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_LANDMARKREPRESENTATION_H
 #define OV_TYPE_LANDMARKREPRESENTATION_H
 
diff --git a/ov_core/src/types/PoseJPL.h b/ov_core/src/types/PoseJPL.h
index 2a80334fd..be8254119 100644
--- a/ov_core/src/types/PoseJPL.h
+++ b/ov_core/src/types/PoseJPL.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_POSEJPL_H
 #define OV_TYPE_TYPE_POSEJPL_H
 
diff --git a/ov_core/src/types/Type.h b/ov_core/src/types/Type.h
index 7c3c810ce..db0a94a52 100644
--- a/ov_core/src/types/Type.h
+++ b/ov_core/src/types/Type.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_BASE_H
 #define OV_TYPE_TYPE_BASE_H
 
diff --git a/ov_core/src/types/Vec.h b/ov_core/src/types/Vec.h
index 86198963a..f5325c264 100644
--- a/ov_core/src/types/Vec.h
+++ b/ov_core/src/types/Vec.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_TYPE_TYPE_VEC_H
 #define OV_TYPE_TYPE_VEC_H
 
diff --git a/ov_core/src/utils/colors.h b/ov_core/src/utils/colors.h
index bf67e9a70..04bb9b623 100644
--- a/ov_core/src/utils/colors.h
+++ b/ov_core/src/utils/colors.h
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #ifndef OV_CORE_COLOR_MACROS
 #define OV_CORE_COLOR_MACROS
 
diff --git a/ov_core/src/utils/dataset_reader.h b/ov_core/src/utils/dataset_reader.h
index 50bbb29d9..9e3da37a1 100644
--- a/ov_core/src/utils/dataset_reader.h
+++ b/ov_core/src/utils/dataset_reader.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_DATASET_READER_H
 #define OV_CORE_DATASET_READER_H
 
diff --git a/ov_core/src/utils/lambda_body.h b/ov_core/src/utils/lambda_body.h
index a4db6b27d..ea3479e9c 100644
--- a/ov_core/src/utils/lambda_body.h
+++ b/ov_core/src/utils/lambda_body.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef LAMBDA_BODY_H
 #define LAMBDA_BODY_H
 
diff --git a/ov_core/src/utils/quat_ops.h b/ov_core/src/utils/quat_ops.h
index 4387a47be..a8989e22c 100644
--- a/ov_core/src/utils/quat_ops.h
+++ b/ov_core/src/utils/quat_ops.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_QUAT_OPS_H
 #define OV_CORE_QUAT_OPS_H
 
diff --git a/ov_core/src/utils/sensor_data.h b/ov_core/src/utils/sensor_data.h
index f44edf196..8aeeb2b0f 100644
--- a/ov_core/src/utils/sensor_data.h
+++ b/ov_core/src/utils/sensor_data.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_CORE_SENSOR_DATA_H
 #define OV_CORE_SENSOR_DATA_H
 
@@ -61,9 +60,12 @@ struct CameraData {
   /// Camera ids for each of the images collected
   std::vector<int> sensor_ids;
 
-  /// Camera ids for each of the images collected
+  /// Raw image we have collected for each camera
   std::vector<cv::Mat> images;
 
+  /// Tracking masks for each camera we have
+  std::vector<cv::Mat> masks;
+
   /// Sort function to allow for using of STL containers
   bool operator<(const CameraData &other) const {
     if (timestamp == other.timestamp) {
diff --git a/ov_data/kaist_vio/circle.txt b/ov_data/kaist_vio/circle.txt
new file mode 100644
index 000000000..5ed29835a
--- /dev/null
+++ b/ov_data/kaist_vio/circle.txt
@@ -0,0 +1,8362 @@
+# timestamp(s) tx ty tz qx qy qz qw Pr11 Pr12 Pr13 Pr22 Pr23 Pr33 Pt11 Pt12 Pt13 Pt22 Pt23 Pt33
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diff --git a/ov_data/kaist_vio/circle_fast.txt b/ov_data/kaist_vio/circle_fast.txt
new file mode 100644
index 000000000..0f6dfda4c
--- /dev/null
+++ b/ov_data/kaist_vio/circle_fast.txt
@@ -0,0 +1,7853 @@
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diff --git a/ov_data/kaist_vio/circle_head.txt b/ov_data/kaist_vio/circle_head.txt
new file mode 100644
index 000000000..cccda0def
--- /dev/null
+++ b/ov_data/kaist_vio/circle_head.txt
@@ -0,0 +1,7011 @@
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diff --git a/ov_data/kaist_vio/infinite.txt b/ov_data/kaist_vio/infinite.txt
new file mode 100644
index 000000000..ab66f151b
--- /dev/null
+++ b/ov_data/kaist_vio/infinite.txt
@@ -0,0 +1,8517 @@
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diff --git a/ov_data/kaist_vio/infinite_fast.txt b/ov_data/kaist_vio/infinite_fast.txt
new file mode 100644
index 000000000..f36628d1c
--- /dev/null
+++ b/ov_data/kaist_vio/infinite_fast.txt
@@ -0,0 +1,9883 @@
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diff --git a/ov_data/kaist_vio/infinite_head.txt b/ov_data/kaist_vio/infinite_head.txt
new file mode 100644
index 000000000..f64e2ff75
--- /dev/null
+++ b/ov_data/kaist_vio/infinite_head.txt
@@ -0,0 +1,7846 @@
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diff --git a/ov_data/kaist_vio/rotation.txt b/ov_data/kaist_vio/rotation.txt
new file mode 100644
index 000000000..35f4691fc
--- /dev/null
+++ b/ov_data/kaist_vio/rotation.txt
@@ -0,0 +1,7801 @@
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diff --git a/ov_data/kaist_vio/rotation_fast.txt b/ov_data/kaist_vio/rotation_fast.txt
new file mode 100644
index 000000000..6bca82ccf
--- /dev/null
+++ b/ov_data/kaist_vio/rotation_fast.txt
@@ -0,0 +1,6779 @@
+# timestamp(s) tx ty tz qx qy qz qw Pr11 Pr12 Pr13 Pr22 Pr23 Pr33 Pt11 Pt12 Pt13 Pt22 Pt23 Pt33
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diff --git a/ov_data/kaist_vio/square.txt b/ov_data/kaist_vio/square.txt
new file mode 100644
index 000000000..bbbc3c55a
--- /dev/null
+++ b/ov_data/kaist_vio/square.txt
@@ -0,0 +1,8775 @@
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diff --git a/ov_data/kaist_vio/square_fast.txt b/ov_data/kaist_vio/square_fast.txt
new file mode 100644
index 000000000..0a0780cec
--- /dev/null
+++ b/ov_data/kaist_vio/square_fast.txt
@@ -0,0 +1,5648 @@
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diff --git a/ov_data/kaist_vio/square_head.txt b/ov_data/kaist_vio/square_head.txt
new file mode 100644
index 000000000..3cde48569
--- /dev/null
+++ b/ov_data/kaist_vio/square_head.txt
@@ -0,0 +1,11419 @@
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+1599133223.17731 -0.241739 0.018038 0.001288 0.000443 -0.003589 -0.006803 0.999970
diff --git a/ov_data/masks/ironsides0.png b/ov_data/masks/ironsides0.png
new file mode 100644
index 000000000..159ddff1b
Binary files /dev/null and b/ov_data/masks/ironsides0.png differ
diff --git a/ov_data/masks/ironsides0.xcf b/ov_data/masks/ironsides0.xcf
new file mode 100644
index 000000000..2465f94c5
Binary files /dev/null and b/ov_data/masks/ironsides0.xcf differ
diff --git a/ov_data/masks/ironsides1.png b/ov_data/masks/ironsides1.png
new file mode 100644
index 000000000..0305a9343
Binary files /dev/null and b/ov_data/masks/ironsides1.png differ
diff --git a/ov_data/masks/ironsides1.xcf b/ov_data/masks/ironsides1.xcf
new file mode 100644
index 000000000..edea919c2
Binary files /dev/null and b/ov_data/masks/ironsides1.xcf differ
diff --git a/ov_data/masks/tumvi0.png b/ov_data/masks/tumvi0.png
new file mode 100644
index 000000000..0eaa66d15
Binary files /dev/null and b/ov_data/masks/tumvi0.png differ
diff --git a/ov_data/masks/tumvi0.xcf b/ov_data/masks/tumvi0.xcf
new file mode 100644
index 000000000..01b1cb94d
Binary files /dev/null and b/ov_data/masks/tumvi0.xcf differ
diff --git a/ov_data/masks/tumvi1.png b/ov_data/masks/tumvi1.png
new file mode 100644
index 000000000..9b47e5676
Binary files /dev/null and b/ov_data/masks/tumvi1.png differ
diff --git a/ov_data/masks/tumvi1.xcf b/ov_data/masks/tumvi1.xcf
new file mode 100644
index 000000000..13dab0076
Binary files /dev/null and b/ov_data/masks/tumvi1.xcf differ
diff --git a/ov_eval/CMakeLists.txt b/ov_eval/CMakeLists.txt
index 9823992c4..3ceae0906 100644
--- a/ov_eval/CMakeLists.txt
+++ b/ov_eval/CMakeLists.txt
@@ -25,15 +25,17 @@ if(PYTHONLIBS_FOUND AND NOT DISABLE_MATPLOTLIB)
 endif()
 
 # Describe catkin project
-if (catkin_FOUND)
+option(ENABLE_CATKIN_ROS "Enable or disable building with ROS (if it is found)" ON)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     add_definitions(-DROS_AVAILABLE=1)
     catkin_package(
             CATKIN_DEPENDS roscpp rospy geometry_msgs nav_msgs sensor_msgs
             INCLUDE_DIRS src
-            LIBRARIES ov_eval_lib
+            LIBRARIES ov_core_lib
     )
 else()
-    message(WARNING "CATKIN NOT FOUND BUILDING WITHOUT ROS!")
+    add_definitions(-DROS_AVAILABLE=0)
+    message(WARNING "BUILDING WITHOUT ROS!")
 endif()
 
 # Try to compile with c++11
@@ -92,9 +94,14 @@ target_link_libraries(ov_eval_lib ${thirdparty_libraries})
 ##################################################
 
 
-if (catkin_FOUND)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
+
     add_executable(pose_to_file src/pose_to_file.cpp)
     target_link_libraries(pose_to_file ov_eval_lib ${thirdparty_libraries})
+
+    add_executable(live_align_trajectory src/live_align_trajectory.cpp)
+    target_link_libraries(live_align_trajectory ov_eval_lib ${thirdparty_libraries})
+
 endif()
 
 
@@ -129,7 +136,7 @@ target_link_libraries(plot_trajectories ov_eval_lib ${thirdparty_libraries})
 ##################################################
 # Python scripts!
 ##################################################
-if (catkin_FOUND)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     catkin_install_python(PROGRAMS python/pid_ros.py DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION})
     catkin_install_python(PROGRAMS python/pid_sys.py DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION})
 endif()
diff --git a/ov_eval/src/alignment/AlignTrajectory.cpp b/ov_eval/src/alignment/AlignTrajectory.cpp
index 041a836e1..99c8d8126 100644
--- a/ov_eval/src/alignment/AlignTrajectory.cpp
+++ b/ov_eval/src/alignment/AlignTrajectory.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "AlignTrajectory.h"
 
 using namespace ov_eval;
diff --git a/ov_eval/src/alignment/AlignTrajectory.h b/ov_eval/src/alignment/AlignTrajectory.h
index 581e2ec6d..dc1b1ff62 100644
--- a/ov_eval/src/alignment/AlignTrajectory.h
+++ b/ov_eval/src/alignment/AlignTrajectory.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_ALIGNTRAJECTORY_H
 #define OV_EVAL_ALIGNTRAJECTORY_H
 
diff --git a/ov_eval/src/alignment/AlignUtils.cpp b/ov_eval/src/alignment/AlignUtils.cpp
index db548c0b2..d12ac8ff1 100644
--- a/ov_eval/src/alignment/AlignUtils.cpp
+++ b/ov_eval/src/alignment/AlignUtils.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "AlignUtils.h"
 
 using namespace ov_eval;
@@ -170,7 +169,7 @@ void AlignUtils::perform_association(double offset, double max_difference, std::
     printf(RED "[ALIGN]: Was unable to associate groundtruth and estimate trajectories\n" RESET);
     printf(RED "[ALIGN]: %d total matches....\n" RESET, (int)est_times.size());
     printf(RED "[ALIGN]: Do the time of the files match??\n" RESET);
-    std::exit(EXIT_FAILURE);
+    return;
   }
   assert(est_times_temp.size() == gt_times_temp.size());
   // printf("[TRAJ]: %d est poses and %d gt poses => %d matches\n",(int)est_times.size(),(int)gt_times.size(),(int)est_times_temp.size());
diff --git a/ov_eval/src/alignment/AlignUtils.h b/ov_eval/src/alignment/AlignUtils.h
index 35d1a74a2..17d8a8e2e 100644
--- a/ov_eval/src/alignment/AlignUtils.h
+++ b/ov_eval/src/alignment/AlignUtils.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_ALIGNUTILS_H
 #define OV_EVAL_ALIGNUTILS_H
 
diff --git a/ov_eval/src/calc/ResultSimulation.cpp b/ov_eval/src/calc/ResultSimulation.cpp
index becef9578..4d5874af4 100644
--- a/ov_eval/src/calc/ResultSimulation.cpp
+++ b/ov_eval/src/calc/ResultSimulation.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "ResultSimulation.h"
 
 using namespace ov_eval;
diff --git a/ov_eval/src/calc/ResultSimulation.h b/ov_eval/src/calc/ResultSimulation.h
index 3a2ca9768..0c3259a52 100644
--- a/ov_eval/src/calc/ResultSimulation.h
+++ b/ov_eval/src/calc/ResultSimulation.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_SIMULATION_H
 #define OV_EVAL_SIMULATION_H
 
diff --git a/ov_eval/src/calc/ResultTrajectory.cpp b/ov_eval/src/calc/ResultTrajectory.cpp
index 937492f33..e0bb7b375 100644
--- a/ov_eval/src/calc/ResultTrajectory.cpp
+++ b/ov_eval/src/calc/ResultTrajectory.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "ResultTrajectory.h"
 
 using namespace ov_eval;
@@ -40,7 +39,7 @@ ResultTrajectory::ResultTrajectory(std::string path_est, std::string path_gt, st
   AlignUtils::perform_association(0, 0.02, est_times, gt_times, est_poses, gt_poses, est_covori, est_covpos, gt_covori, gt_covpos);
 
   // Return failure if we didn't have any common timestamps
-  if (est_poses.size() < 2) {
+  if (est_poses.size() < 3) {
     printf(RED "[TRAJ]: unable to get enough common timestamps between trajectories.\n" RESET);
     printf(RED "[TRAJ]: does the estimated trajectory publish the rosbag timestamps??\n" RESET);
     std::exit(EXIT_FAILURE);
diff --git a/ov_eval/src/calc/ResultTrajectory.h b/ov_eval/src/calc/ResultTrajectory.h
index 39c52b0e0..e38982bc9 100644
--- a/ov_eval/src/calc/ResultTrajectory.h
+++ b/ov_eval/src/calc/ResultTrajectory.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_TRAJECTORY_H
 #define OV_EVAL_TRAJECTORY_H
 
diff --git a/ov_eval/src/dummy.cpp b/ov_eval/src/dummy.cpp
index 24bda194a..d325bb8b8 100644
--- a/ov_eval/src/dummy.cpp
+++ b/ov_eval/src/dummy.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 /**
  * @namespace ov_eval
  *
@@ -44,8 +42,8 @@
  * We recommend that people look at the [rpg_trajectory_evaluation](https://github.com/uzh-rpg/rpg_trajectory_evaluation) toolbox provided
  * by Zhang and Scaramuzza. For a background we recommend reading their [A Tutorial on Quantitative Trajectory Evaluation for
  * Visual(-Inertial) Odometry](http://rpg.ifi.uzh.ch/docs/IROS18_Zhang.pdf) @cite Zhang2018IROS and its use in [A Benchmark Comparison of
- * Monocular Visual-Inertial Odometry Algorithms for Flying Robots](http://rpg.ifi.uzh.ch/docs/ICRA18_Delmerico.pdf) @cite
- * Delmerico2018ICRA.
+ * Monocular Visual-Inertial Odometry Algorithms for Flying Robots](http://rpg.ifi.uzh.ch/docs/ICRA18_Delmerico.pdf)
+ * @cite Delmerico2018ICRA
  *
  *
  */
diff --git a/ov_eval/src/error_comparison.cpp b/ov_eval/src/error_comparison.cpp
index 0dfeb0771..e4656480f 100644
--- a/ov_eval/src/error_comparison.cpp
+++ b/ov_eval/src/error_comparison.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string.hpp>
 #include <boost/filesystem.hpp>
diff --git a/ov_eval/src/error_dataset.cpp b/ov_eval/src/error_dataset.cpp
index be1a0972d..3065dfc39 100644
--- a/ov_eval/src/error_dataset.cpp
+++ b/ov_eval/src/error_dataset.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/filesystem.hpp>
 #include <string>
diff --git a/ov_eval/src/error_simulation.cpp b/ov_eval/src/error_simulation.cpp
index 759978d05..757a6e247 100644
--- a/ov_eval/src/error_simulation.cpp
+++ b/ov_eval/src/error_simulation.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include "calc/ResultSimulation.h"
 #include "utils/Colors.h"
 
diff --git a/ov_eval/src/error_singlerun.cpp b/ov_eval/src/error_singlerun.cpp
index 1ff818fe4..179bec23c 100644
--- a/ov_eval/src/error_singlerun.cpp
+++ b/ov_eval/src/error_singlerun.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/filesystem.hpp>
 #include <string>
diff --git a/ov_eval/src/format_converter.cpp b/ov_eval/src/format_converter.cpp
index d3508119e..38f9451ee 100644
--- a/ov_eval/src/format_converter.cpp
+++ b/ov_eval/src/format_converter.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string/predicate.hpp>
 #include <boost/filesystem.hpp>
diff --git a/ov_eval/src/live_align_trajectory.cpp b/ov_eval/src/live_align_trajectory.cpp
new file mode 100644
index 000000000..628793d67
--- /dev/null
+++ b/ov_eval/src/live_align_trajectory.cpp
@@ -0,0 +1,137 @@
+/*
+ * OpenVINS: An Open Platform for Visual-Inertial Research
+ * Copyright (C) 2021 Patrick Geneva
+ * Copyright (C) 2021 Guoquan Huang
+ * Copyright (C) 2021 OpenVINS Contributors
+ * Copyright (C) 2019 Kevin Eckenhoff
+ *
+ * This program is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <https://www.gnu.org/licenses/>.
+ */
+
+#include <geometry_msgs/PoseStamped.h>
+#include <nav_msgs/Path.h>
+#include <ros/ros.h>
+
+#include "alignment/AlignTrajectory.h"
+#include "alignment/AlignUtils.h"
+#include "utils/Colors.h"
+#include "utils/Loader.h"
+#include "utils/Math.h"
+
+ros::Publisher pub_path;
+void align_and_publish(const nav_msgs::Path::ConstPtr &msg);
+std::vector<double> times_gt;
+std::vector<Eigen::Matrix<double, 7, 1>> poses_gt;
+std::string alignment_type;
+
+int main(int argc, char **argv) {
+
+  // Create ros node
+  ros::init(argc, argv, "live_align_trajectory");
+  ros::NodeHandle nh("~");
+
+  // Load what type of alignment we should use
+  nh.param<std::string>("alignment_type", alignment_type, "posyaw");
+
+  // If we don't have it, or it is empty then error
+  if (!nh.hasParam("path_gt")) {
+    ROS_ERROR("[LOAD]: Please provide a groundtruth file path!!!");
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Load our groundtruth from file
+  std::string path_to_gt;
+  nh.param<std::string>("path_gt", path_to_gt, "");
+  boost::filesystem::path infolder(path_to_gt);
+  if (infolder.extension() == ".csv") {
+    std::vector<Eigen::Matrix3d> cov_ori_temp, cov_pos_temp;
+    ov_eval::Loader::load_data_csv(path_to_gt, times_gt, poses_gt, cov_ori_temp, cov_pos_temp);
+  } else {
+    std::vector<Eigen::Matrix3d> cov_ori_temp, cov_pos_temp;
+    ov_eval::Loader::load_data(path_to_gt, times_gt, poses_gt, cov_ori_temp, cov_pos_temp);
+  }
+
+  // Our subscribe and publish nodes
+  ros::Subscriber sub = nh.subscribe("/ov_msckf/pathimu", 1, align_and_publish);
+  pub_path = nh.advertise<nav_msgs::Path>("/ov_msckf/pathgt", 2);
+  ROS_INFO("Subscribing: %s", sub.getTopic().c_str());
+  ROS_INFO("Publishing: %s", pub_path.getTopic().c_str());
+
+  // Spin
+  ros::spin();
+}
+
+void align_and_publish(const nav_msgs::Path::ConstPtr &msg) {
+
+  // Convert the message into correct vector format
+  // tx ty tz qx qy qz qw
+  std::vector<double> times_temp;
+  std::vector<Eigen::Matrix<double, 7, 1>> poses_temp;
+  for (auto const &pose : msg->poses) {
+    times_temp.push_back(pose.header.stamp.toSec());
+    Eigen::Matrix<double, 7, 1> pose_tmp;
+    pose_tmp << pose.pose.position.x, pose.pose.position.y, pose.pose.position.z, pose.pose.orientation.x, pose.pose.orientation.y,
+        pose.pose.orientation.z, pose.pose.orientation.w;
+    poses_temp.push_back(pose_tmp);
+  }
+
+  // Intersect timestamps
+  std::vector<double> gt_times_temp = times_gt;
+  std::vector<Eigen::Matrix<double, 7, 1>> gt_poses_temp = poses_gt;
+  ov_eval::AlignUtils::perform_association(0, 0.02, times_temp, gt_times_temp, poses_temp, gt_poses_temp);
+
+  // Return failure if we didn't have any common timestamps
+  if (poses_temp.size() < 3) {
+    printf(RED "[TRAJ]: unable to get enough common timestamps between trajectories.\n" RESET);
+    printf(RED "[TRAJ]: does the estimated trajectory publish the rosbag timestamps??\n" RESET);
+    return;
+  }
+
+  // Perform alignment of the trajectories
+  Eigen::Matrix3d R_ESTtoGT;
+  Eigen::Vector3d t_ESTinGT;
+  double s_ESTtoGT;
+  ov_eval::AlignTrajectory::align_trajectory(poses_temp, gt_poses_temp, R_ESTtoGT, t_ESTinGT, s_ESTtoGT, alignment_type);
+  Eigen::Vector4d q_ESTtoGT = ov_eval::Math::rot_2_quat(R_ESTtoGT);
+  printf("[TRAJ]: q_ESTtoGT = %.3f, %.3f, %.3f, %.3f | p_ESTinGT = %.3f, %.3f, %.3f | s = %.2f\n", q_ESTtoGT(0), q_ESTtoGT(1), q_ESTtoGT(2),
+         q_ESTtoGT(3), t_ESTinGT(0), t_ESTinGT(1), t_ESTinGT(2), s_ESTtoGT);
+
+  // Finally lets calculate the aligned trajectories
+  // TODO: maybe in the future we could live publish trajectory errors...
+  // NOTE: We downsample the number of poses as needed to prevent rviz crashes
+  // NOTE: https://github.com/ros-visualization/rviz/issues/1107
+  nav_msgs::Path arr_groundtruth;
+  arr_groundtruth.header = msg->header;
+  for (size_t i = 0; i < gt_times_temp.size(); i += std::floor(gt_times_temp.size() / 16384.0) + 1) {
+
+    // Convert into the correct frame
+    double timestamp = gt_times_temp.at(i);
+    Eigen::Matrix<double, 7, 1> pose_inGT = gt_poses_temp.at(i);
+    Eigen::Vector3d pos_IinEST = R_ESTtoGT.transpose() * (pose_inGT.block(0, 0, 3, 1) - t_ESTinGT) / s_ESTtoGT;
+    Eigen::Vector4d quat_ESTtoI = ov_eval::Math::quat_multiply(pose_inGT.block(3, 0, 4, 1), q_ESTtoGT);
+    // Finally push back
+    geometry_msgs::PoseStamped posetemp;
+    posetemp.header = msg->header;
+    posetemp.header.stamp = ros::Time(timestamp);
+    posetemp.pose.orientation.x = quat_ESTtoI(0);
+    posetemp.pose.orientation.y = quat_ESTtoI(1);
+    posetemp.pose.orientation.z = quat_ESTtoI(2);
+    posetemp.pose.orientation.w = quat_ESTtoI(3);
+    posetemp.pose.position.x = pos_IinEST(0);
+    posetemp.pose.position.y = pos_IinEST(1);
+    posetemp.pose.position.z = pos_IinEST(2);
+    arr_groundtruth.poses.push_back(posetemp);
+  }
+  pub_path.publish(arr_groundtruth);
+}
diff --git a/ov_eval/src/plot_trajectories.cpp b/ov_eval/src/plot_trajectories.cpp
index 1592bd131..ea49c690f 100644
--- a/ov_eval/src/plot_trajectories.cpp
+++ b/ov_eval/src/plot_trajectories.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string/predicate.hpp>
 #include <boost/filesystem.hpp>
@@ -116,7 +114,7 @@ int main(int argc, char **argv) {
       ov_eval::AlignUtils::perform_association(0, 0.02, times_temp, gt_times_temp, poses_temp, gt_poses_temp);
 
       // Return failure if we didn't have any common timestamps
-      if (poses_temp.size() < 2) {
+      if (poses_temp.size() < 3) {
         printf(RED "[TRAJ]: unable to get enough common timestamps between trajectories.\n" RESET);
         printf(RED "[TRAJ]: does the estimated trajectory publish the rosbag timestamps??\n" RESET);
         std::exit(EXIT_FAILURE);
diff --git a/ov_eval/src/pose_to_file.cpp b/ov_eval/src/pose_to_file.cpp
index 1645ef4c3..a96036059 100644
--- a/ov_eval/src/pose_to_file.cpp
+++ b/ov_eval/src/pose_to_file.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <geometry_msgs/PoseStamped.h>
 #include <geometry_msgs/PoseWithCovarianceStamped.h>
 #include <geometry_msgs/TransformStamped.h>
diff --git a/ov_eval/src/timing_comparison.cpp b/ov_eval/src/timing_comparison.cpp
index d41ab2a21..41bd29288 100644
--- a/ov_eval/src/timing_comparison.cpp
+++ b/ov_eval/src/timing_comparison.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string/predicate.hpp>
 #include <boost/filesystem.hpp>
diff --git a/ov_eval/src/timing_flamegraph.cpp b/ov_eval/src/timing_flamegraph.cpp
index fd5ccebf8..4dea53d6a 100644
--- a/ov_eval/src/timing_flamegraph.cpp
+++ b/ov_eval/src/timing_flamegraph.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string/predicate.hpp>
 #include <boost/filesystem.hpp>
diff --git a/ov_eval/src/timing_percentages.cpp b/ov_eval/src/timing_percentages.cpp
index 79f0f31ba..79dc8d8bb 100644
--- a/ov_eval/src/timing_percentages.cpp
+++ b/ov_eval/src/timing_percentages.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <Eigen/Eigen>
 #include <boost/algorithm/string/predicate.hpp>
 #include <boost/filesystem.hpp>
diff --git a/ov_eval/src/utils/Colors.h b/ov_eval/src/utils/Colors.h
index 9bc50759f..033c51ad7 100644
--- a/ov_eval/src/utils/Colors.h
+++ b/ov_eval/src/utils/Colors.h
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #ifndef OV_CORE_COLOR_MACROS
 #define OV_CORE_COLOR_MACROS
 
diff --git a/ov_eval/src/utils/Loader.cpp b/ov_eval/src/utils/Loader.cpp
index e79bf6746..ab45d21aa 100644
--- a/ov_eval/src/utils/Loader.cpp
+++ b/ov_eval/src/utils/Loader.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "Loader.h"
 
 using namespace ov_eval;
@@ -107,6 +106,76 @@ void Loader::load_data(std::string path_traj, std::vector<double> &times, std::v
   // printf("[LOAD]: loaded %d poses from %s\n",(int)poses.size(),base_filename.c_str());
 }
 
+void Loader::load_data_csv(std::string path_traj, std::vector<double> &times, std::vector<Eigen::Matrix<double, 7, 1>> &poses,
+                           std::vector<Eigen::Matrix3d> &cov_ori, std::vector<Eigen::Matrix3d> &cov_pos) {
+
+  // Try to open our trajectory file
+  std::ifstream file(path_traj);
+  if (!file.is_open()) {
+    printf(RED "[LOAD]: Unable to open trajectory file...\n" RESET);
+    printf(RED "[LOAD]: %s\n" RESET, path_traj.c_str());
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Loop through each line of this file
+  std::string current_line;
+  while (std::getline(file, current_line)) {
+
+    // Skip if we start with a comment
+    if (!current_line.find("#"))
+      continue;
+
+    // Loop variables
+    int i = 0;
+    std::istringstream s(current_line);
+    std::string field;
+    Eigen::Matrix<double, 20, 1> data;
+
+    // Loop through this line (groundtruth state [time(sec),q_GtoI,p_IinG,v_IinG,b_gyro,b_accel])
+    while (std::getline(s, field, ',')) {
+      // Skip if empty
+      if (field.empty() || i >= data.rows())
+        continue;
+      // save the data to our vector
+      data(i) = std::atof(field.c_str());
+      i++;
+    }
+
+    // Only a valid line if we have all the parameters
+    // Times are in nanoseconds -> convert to seconds
+    // Our "fixed" state vector from the ETH GT format [q,p,v,bg,ba]
+    if (i >= 8) {
+      times.push_back(1e-9 * data(0));
+      Eigen::Matrix<double, 7, 1> imustate;
+      imustate(0, 0) = data(1, 0); // pos
+      imustate(1, 0) = data(2, 0);
+      imustate(2, 0) = data(3, 0);
+      imustate(3, 0) = data(5, 0); // quat (xyzw)
+      imustate(4, 0) = data(6, 0);
+      imustate(5, 0) = data(7, 0);
+      imustate(6, 0) = data(4, 0);
+      poses.push_back(imustate);
+    }
+  }
+
+  // Finally close the file
+  file.close();
+
+  // Error if we don't have any data
+  if (times.empty()) {
+    printf(RED "[LOAD]: Could not parse any data from the file!!\n" RESET);
+    printf(RED "[LOAD]: %s\n" RESET, path_traj.c_str());
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Assert that they are all equal
+  if (times.size() != poses.size()) {
+    printf(RED "[LOAD]: Parsing error, pose and timestamps do not match!!\n" RESET);
+    printf(RED "[LOAD]: %s\n" RESET, path_traj.c_str());
+    std::exit(EXIT_FAILURE);
+  }
+}
+
 void Loader::load_simulation(std::string path, std::vector<Eigen::VectorXd> &values) {
 
   // Try to open our trajectory file
diff --git a/ov_eval/src/utils/Loader.h b/ov_eval/src/utils/Loader.h
index b16b948a6..d06a54fc8 100644
--- a/ov_eval/src/utils/Loader.h
+++ b/ov_eval/src/utils/Loader.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_LOADER_H
 #define OV_EVAL_LOADER_H
 
@@ -51,6 +50,17 @@ class Loader {
   static void load_data(std::string path_traj, std::vector<double> &times, std::vector<Eigen::Matrix<double, 7, 1>> &poses,
                         std::vector<Eigen::Matrix3d> &cov_ori, std::vector<Eigen::Matrix3d> &cov_pos);
 
+  /**
+   * @brief This will load *comma* separated trajectory into memory (ASL/ETH format)
+   * @param path_traj Path to the trajectory file that we want to read in.
+   * @param times Timesteps in seconds for each pose
+   * @param poses Pose at every timestep [pos,quat]
+   * @param cov_ori Vector of orientation covariances at each timestep (empty if we can't load)
+   * @param cov_pos Vector of position covariances at each timestep (empty if we can't load)
+   */
+  static void load_data_csv(std::string path_traj, std::vector<double> &times, std::vector<Eigen::Matrix<double, 7, 1>> &poses,
+                            std::vector<Eigen::Matrix3d> &cov_ori, std::vector<Eigen::Matrix3d> &cov_pos);
+
   /**
    * @brief Load an arbitrary sized row of *space* separated values, used for our simulation
    * @param path Path to our text file to load
diff --git a/ov_eval/src/utils/Math.h b/ov_eval/src/utils/Math.h
index 8dc42faf1..6cc8fc81f 100644
--- a/ov_eval/src/utils/Math.h
+++ b/ov_eval/src/utils/Math.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_MATH_H
 #define OV_EVAL_MATH_H
 
diff --git a/ov_eval/src/utils/Recorder.h b/ov_eval/src/utils/Recorder.h
index 21298cd7f..b92b4d292 100644
--- a/ov_eval/src/utils/Recorder.h
+++ b/ov_eval/src/utils/Recorder.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_RECORDER_H
 #define OV_EVAL_RECORDER_H
 
diff --git a/ov_eval/src/utils/Statistics.h b/ov_eval/src/utils/Statistics.h
index 264fa1e79..af2a1a839 100644
--- a/ov_eval/src/utils/Statistics.h
+++ b/ov_eval/src/utils/Statistics.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_EVAL_STATISTICS_H
 #define OV_EVAL_STATISTICS_H
 
diff --git a/ov_msckf/CMakeLists.txt b/ov_msckf/CMakeLists.txt
index 56095dddb..169e77573 100644
--- a/ov_msckf/CMakeLists.txt
+++ b/ov_msckf/CMakeLists.txt
@@ -17,13 +17,22 @@ if (NOT OpenCV_FOUND)
 endif()
 find_package(Boost REQUIRED COMPONENTS system filesystem thread date_time)
 
-# display message to user
-#message(WARNING "EIGEN VERSION: " ${EIGEN3_VERSION})
+# Display message to user
 message(WARNING "OPENCV VERSION: " ${OpenCV_VERSION})
 message(WARNING "BOOST VERSION: " ${Boost_VERSION})
 
+# If we will compile with aruco support
+option(ENABLE_ARUCO_TAGS "Enable or disable aruco tag (disable if no contrib modules)" ON)
+if (NOT ENABLE_ARUCO_TAGS)
+    add_definitions(-DENABLE_ARUCO_TAGS=0)
+    message(WARNING "DISABLING ARUCOTAG TRACKING!")
+else()
+    add_definitions(-DENABLE_ARUCO_TAGS=1)
+endif()
+
 # Describe catkin project
-if (catkin_FOUND)
+option(ENABLE_CATKIN_ROS "Enable or disable building with ROS (if it is found)" ON)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     add_definitions(-DROS_AVAILABLE=1)
     catkin_package(
             CATKIN_DEPENDS roscpp rosbag tf std_msgs geometry_msgs sensor_msgs nav_msgs visualization_msgs cv_bridge ov_core
@@ -31,7 +40,8 @@ if (catkin_FOUND)
             LIBRARIES ov_msckf_lib
     )
 else()
-    message(WARNING "CATKIN NOT FOUND BUILDING WITHOUT ROS!")
+    add_definitions(-DROS_AVAILABLE=0)
+    message(WARNING "BUILDING WITHOUT ROS!")
 endif()
 
 # Try to compile with c++11
@@ -71,7 +81,7 @@ list(APPEND thirdparty_libraries
 # If we are not building with ROS then we need to manually link to its headers
 # This isn't that elegant of a way, but this at least allows for building without ROS
 # See this stackoverflow answer: https://stackoverflow.com/a/11217008/7718197
-if (NOT catkin_FOUND)
+if (NOT catkin_FOUND OR NOT ENABLE_CATKIN_ROS)
     message(WARNING "MANUALLY LINKING TO OV_CORE LIBRARY....")
     include_directories(${ov_core_SOURCE_DIR}/src/)
     list(APPEND thirdparty_libraries ov_core_lib)
@@ -91,7 +101,7 @@ list(APPEND library_source_files
         src/update/UpdaterSLAM.cpp
         src/update/UpdaterZeroVelocity.cpp
 )
-if (catkin_FOUND)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
     list(APPEND library_source_files
         src/core/RosVisualizer.cpp
     )
@@ -106,7 +116,7 @@ target_include_directories(ov_msckf_lib PUBLIC src)
 ##################################################
 
 
-if (catkin_FOUND)
+if (catkin_FOUND AND ENABLE_CATKIN_ROS)
 
     add_executable(run_serial_msckf src/ros_serial_msckf.cpp)
     target_link_libraries(run_serial_msckf ov_msckf_lib ${thirdparty_libraries})
diff --git a/ov_msckf/launch/display.rviz b/ov_msckf/launch/display.rviz
index a0c8e1579..8d449e878 100644
--- a/ov_msckf/launch/display.rviz
+++ b/ov_msckf/launch/display.rviz
@@ -5,7 +5,7 @@ Panels:
     Property Tree Widget:
       Expanded: ~
       Splitter Ratio: 0.6011396050453186
-    Tree Height: 161
+    Tree Height: 169
   - Class: rviz/Selection
     Name: Selection
   - Class: rviz/Tool Properties
@@ -24,7 +24,7 @@ Panels:
     Experimental: false
     Name: Time
     SyncMode: 0
-    SyncSource: Image
+    SyncSource: ""
 Preferences:
   PromptSaveOnExit: true
 Toolbars:
@@ -55,34 +55,14 @@ Visualization Manager:
       Frame Timeout: 999
       Frames:
         All Enabled: true
-        cam0:
-          Value: true
-        cam1:
-          Value: true
-        cam2:
-          Value: true
-        cam3:
-          Value: true
-        global:
-          Value: true
-        imu:
-          Value: true
-        truth:
-          Value: true
+      Marker Alpha: 1
       Marker Scale: 1
       Name: TF
       Show Arrows: false
       Show Axes: true
       Show Names: true
       Tree:
-        global:
-          imu:
-            cam0:
-              {}
-            cam1:
-              {}
-          truth:
-            {}
+        {}
       Update Interval: 0
       Value: true
     - Class: rviz/Image
@@ -114,6 +94,7 @@ Visualization Manager:
         Z: 0
       Pose Color: 255; 85; 255
       Pose Style: None
+      Queue Size: 10
       Radius: 0.029999999329447746
       Shaft Diameter: 0.10000000149011612
       Shaft Length: 0.10000000149011612
@@ -137,6 +118,7 @@ Visualization Manager:
         Z: 0
       Pose Color: 255; 85; 255
       Pose Style: None
+      Queue Size: 10
       Radius: 0.029999999329447746
       Shaft Diameter: 0.10000000149011612
       Shaft Length: 0.10000000149011612
@@ -158,9 +140,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: MSCKF Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -188,9 +168,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: SLAM Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -218,9 +196,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: ARUCO Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -248,9 +224,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: ACTIVE Features
       Position Transformer: XYZ
       Queue Size: 10
@@ -278,9 +252,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: SIM Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -333,37 +305,37 @@ Visualization Manager:
   Views:
     Current:
       Class: rviz/Orbit
-      Distance: 12.92563247680664
+      Distance: 19.73822784423828
       Enable Stereo Rendering:
         Stereo Eye Separation: 0.05999999865889549
         Stereo Focal Distance: 1
         Swap Stereo Eyes: false
         Value: false
+      Field of View: 0.7853981852531433
       Focal Point:
-        X: -0.634434700012207
-        Y: -2.0766103267669678
-        Z: 0.8430783748626709
+        X: 0
+        Y: 0
+        Z: 0
       Focal Shape Fixed Size: false
       Focal Shape Size: 0.05000000074505806
       Invert Z Axis: false
       Name: Current View
       Near Clip Distance: 0.009999999776482582
-      Pitch: 0.7053985595703125
+      Pitch: 0.710398256778717
       Target Frame: <Fixed Frame>
-      Value: Orbit (rviz)
-      Yaw: 2.295398473739624
+      Yaw: 0.8253981471061707
     Saved: ~
 Window Geometry:
   Current Depths:
     collapsed: false
   Displays:
     collapsed: false
-  Height: 1023
+  Height: 837
   Hide Left Dock: false
   Hide Right Dock: true
   Image:
     collapsed: false
-  QMainWindow State: 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
+  QMainWindow State: 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
   Selection:
     collapsed: false
   Time:
@@ -372,6 +344,6 @@ Window Geometry:
     collapsed: false
   Views:
     collapsed: true
-  Width: 1867
-  X: 53
-  Y: 27
+  Width: 1779
+  X: 2299
+  Y: 1232
diff --git a/ov_msckf/launch/display_driving.rviz b/ov_msckf/launch/display_driving.rviz
index 035b89508..034f0c026 100644
--- a/ov_msckf/launch/display_driving.rviz
+++ b/ov_msckf/launch/display_driving.rviz
@@ -5,7 +5,7 @@ Panels:
     Property Tree Widget:
       Expanded: ~
       Splitter Ratio: 0.6000000238418579
-    Tree Height: 526
+    Tree Height: 467
   - Class: rviz/Selection
     Name: Selection
   - Class: rviz/Tool Properties
@@ -24,7 +24,7 @@ Panels:
     Experimental: false
     Name: Time
     SyncMode: 0
-    SyncSource: Image
+    SyncSource: ""
 Preferences:
   PromptSaveOnExit: true
 Toolbars:
@@ -55,34 +55,14 @@ Visualization Manager:
       Frame Timeout: 999
       Frames:
         All Enabled: true
-        cam0:
-          Value: true
-        cam1:
-          Value: true
-        cam2:
-          Value: true
-        cam3:
-          Value: true
-        global:
-          Value: true
-        imu:
-          Value: true
-        truth:
-          Value: true
+      Marker Alpha: 1
       Marker Scale: 50
       Name: TF
       Show Arrows: false
       Show Axes: true
       Show Names: true
       Tree:
-        global:
-          imu:
-            cam0:
-              {}
-            cam1:
-              {}
-          truth:
-            {}
+        {}
       Update Interval: 0
       Value: true
     - Class: rviz/Image
@@ -114,6 +94,7 @@ Visualization Manager:
         Z: 0
       Pose Color: 255; 85; 255
       Pose Style: None
+      Queue Size: 10
       Radius: 0.029999999329447746
       Shaft Diameter: 0.10000000149011612
       Shaft Length: 0.10000000149011612
@@ -137,6 +118,7 @@ Visualization Manager:
         Z: 0
       Pose Color: 255; 85; 255
       Pose Style: None
+      Queue Size: 10
       Radius: 0.029999999329447746
       Shaft Diameter: 0.10000000149011612
       Shaft Length: 0.10000000149011612
@@ -158,9 +140,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: MSCKF Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -188,9 +168,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: SLAM Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -218,9 +196,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: ARUCO Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -248,9 +224,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: SIM Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -278,9 +252,7 @@ Visualization Manager:
       Enabled: true
       Invert Rainbow: false
       Max Color: 255; 255; 255
-      Max Intensity: 4096
       Min Color: 0; 0; 0
-      Min Intensity: 0
       Name: Active Points
       Position Transformer: XYZ
       Queue Size: 10
@@ -320,7 +292,7 @@ Visualization Manager:
   Value: true
   Views:
     Current:
-      Angle: 3.2950031757354736
+      Angle: 0
       Class: rviz/TopDownOrtho
       Enable Stereo Rendering:
         Stereo Eye Separation: 0.05999999865889549
@@ -330,21 +302,20 @@ Visualization Manager:
       Invert Z Axis: false
       Name: Current View
       Near Clip Distance: 0.009999999776482582
-      Scale: 2.7952473163604736
+      Scale: 2.45080828666687
       Target Frame: imu
-      Value: TopDownOrtho (rviz)
       X: 0
       Y: 0
     Saved: ~
 Window Geometry:
   Displays:
     collapsed: false
-  Height: 1052
+  Height: 972
   Hide Left Dock: false
   Hide Right Dock: true
   Image:
     collapsed: false
-  QMainWindow State: 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
+  QMainWindow State: 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
   Selection:
     collapsed: false
   Time:
@@ -353,6 +324,6 @@ Window Geometry:
     collapsed: false
   Views:
     collapsed: true
-  Width: 1920
-  X: 0
-  Y: 0
+  Width: 1707
+  X: 2243
+  Y: 1301
diff --git a/ov_msckf/launch/pgeneva_ros_eth.launch b/ov_msckf/launch/pgeneva_ros_eth.launch
index cc980e5d1..394ef9fe0 100644
--- a/ov_msckf/launch/pgeneva_ros_eth.launch
+++ b/ov_msckf/launch/pgeneva_ros_eth.launch
@@ -4,7 +4,9 @@
     <arg name="max_cameras" default="2" />
     <arg name="use_stereo"  default="true" />
     <arg name="bag_start"   default="0" /> <!-- v1-2: 0, mh1: 40, mh2: 35, mh3: 17.5, mh4-5: 15 -->
-    <arg name="bag"         default="/home/patrick/datasets/eth/V1_01_easy.bag" />
+    <arg name="dataset"     default="V1_02_medium" /> <!-- V1_01_easy, V1_02_medium, V2_02_medium -->
+    <arg name="bag"         default="/home/patrick/datasets/eth/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/euroc_mav/$(arg dataset).csv" />
 
     <!-- imu starting thresholds -->
     <arg name="init_window_time"  default="0.75" />
@@ -25,7 +27,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- world/filter parameters -->
         <param name="use_fej"                type="bool"   value="true" />
@@ -72,6 +73,7 @@
         <param name="knn_ratio"          type="double" value="0.70" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="false" />
@@ -125,6 +127,12 @@
     <!-- play the dataset -->
     <node pkg="rosbag" type="play" name="rosbag" args="-d 1 -s $(arg bag_start) $(arg bag)" required="true"/>
 
+    <!-- path viz of aligned gt -->
+    <node name="live_align_trajectory" pkg="ov_eval" type="live_align_trajectory" output="log" clear_params="true">
+        <param name="alignment_type" type="str" value="posyaw" />
+        <param name="path_gt"        type="str" value="$(arg bag_gt)" />
+    </node>
+
     <!-- record the trajectory if enabled -->
     <group if="$(arg dosave)">
         <node name="recorder_estimate" pkg="ov_eval" type="pose_to_file" output="screen" required="true">
diff --git a/ov_msckf/launch/pgeneva_ros_kaist.launch b/ov_msckf/launch/pgeneva_ros_kaist.launch
index 1736e0749..4cb02c993 100644
--- a/ov_msckf/launch/pgeneva_ros_kaist.launch
+++ b/ov_msckf/launch/pgeneva_ros_kaist.launch
@@ -10,6 +10,8 @@
     <arg name="path_est"    default="/tmp/traj_estimate.txt" />
     <arg name="path_time"   default="/tmp/traj_timing.txt" />
 
+    <!-- groundtruth information -->
+    <arg name="bag_gt"      default="$(find ov_data)/kaist/urban39.csv" /> <!-- urban28, urban38, urban39 -->
 
     <!-- MASTER NODE! -->
 <!--    <node name="run_subscribe_msckf" pkg="ov_msckf" type="run_subscribe_msckf" output="screen" clear_params="true" required="true" launch-prefix="gdb -ex run &#45;&#45;args">-->
@@ -19,7 +21,6 @@
         <param name="topic_imu"      type="string" value="/imu/data_raw" />
         <param name="topic_camera0"  type="string" value="/stereo/left/image_raw" />
         <param name="topic_camera1"  type="string" value="/stereo/right/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- world/filter parameters -->
         <param name="use_fej"                type="bool"   value="true" />
@@ -66,6 +67,7 @@
         <param name="knn_ratio"          type="double" value="0.70" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
 
         <param name="fi_max_dist"        type="double" value="500" />
         <param name="fi_max_baseline"    type="double" value="120" />
@@ -123,6 +125,12 @@
 
     </node>
 
+    <!-- path viz of aligned gt -->
+    <node name="live_align_trajectory" pkg="ov_eval" type="live_align_trajectory" output="log" clear_params="true">
+        <param name="alignment_type" type="str" value="posyaw" />
+        <param name="path_gt"        type="str" value="$(arg bag_gt)" />
+    </node>
+
     <!-- record the trajectory if enabled -->
     <group if="$(arg dosave)">
         <node name="recorder_estimate" pkg="ov_eval" type="pose_to_file" output="screen" required="true">
diff --git a/ov_msckf/launch/pgeneva_ros_kaistvio.launch b/ov_msckf/launch/pgeneva_ros_kaistvio.launch
new file mode 100644
index 000000000..808a8ff8c
--- /dev/null
+++ b/ov_msckf/launch/pgeneva_ros_kaistvio.launch
@@ -0,0 +1,154 @@
+<launch>
+
+    <!-- mono or stereo and what ros bag to play -->
+    <arg name="max_cameras" default="2" />
+    <arg name="use_stereo"  default="true" />
+    <arg name="bag_start"   default="40" />
+    <arg name="dataset"     default="rotation" /> <!-- circle, circle_fast, circle_head, square, square_fast, square_head -->
+    <arg name="bag"         default="/media/patrick/RPNG\ FLASH\ 3/KAIST_VIO/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/kaist_vio/$(arg dataset).txt" /> <!-- $(find ov_data)/kaist_vio/$(arg dataset).txt -->
+
+    <!-- imu starting thresholds -->
+    <arg name="init_window_time"  default="1.5" />
+    <arg name="init_imu_thresh"   default="0.1" />
+
+    <!-- saving trajectory path and timing information -->
+    <arg name="dosave"      default="false" />
+    <arg name="dotime"      default="false" />
+    <arg name="path_est"    default="/tmp/traj_estimate.txt" />
+    <arg name="path_time"   default="/tmp/traj_timing.txt" />
+
+
+    <!-- MASTER NODE! -->
+<!--    <node name="run_subscribe_msckf" pkg="ov_msckf" type="run_subscribe_msckf" output="screen" clear_params="true" required="true" launch-prefix="gdb -ex run &#45;&#45;args">-->
+    <node name="run_subscribe_msckf" pkg="ov_msckf" type="run_subscribe_msckf" output="screen" clear_params="true" required="true">
+
+        <!-- bag topics -->
+        <param name="topic_imu"      type="string" value="/mavros/imu/data" />
+        <param name="topic_camera0"  type="string" value="/camera/infra1/image_rect_raw" />
+        <param name="topic_camera1"  type="string" value="/camera/infra2/image_rect_raw" />
+
+        <!-- world/filter parameters -->
+        <param name="use_fej"                type="bool"   value="true" />
+        <param name="use_imuavg"             type="bool"   value="true" />
+        <param name="use_rk4int"             type="bool"   value="true" />
+        <param name="use_stereo"             type="bool"   value="$(arg use_stereo)" />
+        <param name="calib_cam_extrinsics"   type="bool"   value="false" /> <!-- degenerate motion causes this to fail (could use a smaller prior...) -->
+        <param name="calib_cam_intrinsics"   type="bool"   value="true" />
+        <param name="calib_cam_timeoffset"   type="bool"   value="true" />
+        <param name="calib_camimu_dt"        type="double" value="-0.029958533056650416" />
+        <param name="max_clones"             type="int"    value="11" />
+        <param name="max_slam"               type="int"    value="50" />
+        <param name="max_slam_in_update"     type="int"    value="25" /> <!-- 25 seems to work well -->
+        <param name="max_msckf_in_update"    type="int"    value="40" />
+        <param name="max_cameras"            type="int"    value="$(arg max_cameras)" />
+        <param name="dt_slam_delay"          type="double" value="1" />
+        <param name="init_window_time"       type="double" value="$(arg init_window_time)" />
+        <param name="init_imu_thresh"        type="double" value="$(arg init_imu_thresh)" />
+        <param name="gravity_mag"            type="double" value="9.79858" /> <!-- 9.79858 -->
+        <param name="feat_rep_msckf"         type="string" value="GLOBAL_3D" />
+        <param name="feat_rep_slam"          type="string" value="ANCHORED_FULL_INVERSE_DEPTH" />
+        <param name="feat_rep_aruco"         type="string" value="ANCHORED_FULL_INVERSE_DEPTH" />
+
+        <!-- zero velocity update parameters -->
+        <!-- inertial and disparity based detection (inertial is key for dynamic environments) -->
+        <param name="try_zupt"               type="bool"   value="true" />
+        <param name="zupt_chi2_multipler"    type="double" value="0" /> <!-- set to 0 for only disp-based -->
+        <param name="zupt_max_velocity"      type="double" value="0.1" />
+        <param name="zupt_noise_multiplier"  type="double" value="50" />
+        <param name="zupt_max_disparity"     type="double" value="0.2" /> <!-- set to 0 for only imu-based -->
+        <param name="zupt_only_at_beginning" type="bool"   value="false" />
+
+        <!-- timing statistics recording -->
+        <param name="record_timing_information"   type="bool"   value="$(arg dotime)" />
+        <param name="record_timing_filepath"      type="string" value="$(arg path_time)" />
+
+        <!-- tracker/extractor properties -->
+        <param name="use_klt"            type="bool"   value="true" />
+        <param name="num_pts"            type="int"    value="250" />
+        <param name="fast_threshold"     type="int"    value="15" />
+        <param name="grid_x"             type="int"    value="5" />
+        <param name="grid_y"             type="int"    value="3" />
+        <param name="min_px_dist"        type="int"    value="8" />
+        <param name="knn_ratio"          type="double" value="0.70" />
+        <param name="downsample_cameras" type="bool"   value="false" />
+        <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
+
+        <param name="fi_max_baseline"    type="double" value="120" />
+        <param name="fi_max_cond_number" type="double" value="90000" />
+
+        <!-- aruco tag/mapping properties -->
+        <param name="use_aruco"        type="bool"   value="false" />
+        <param name="num_aruco"        type="int"    value="1024" />
+        <param name="downsize_aruco"   type="bool"   value="true" />
+
+        <!-- sensor noise values / update -->
+        <param name="up_msckf_sigma_px"            type="double"   value="1" />
+        <param name="up_msckf_chi2_multipler"      type="double"   value="1" />
+        <param name="up_slam_sigma_px"             type="double"   value="1" />
+        <param name="up_slam_chi2_multipler"       type="double"   value="1" />
+        <param name="up_aruco_sigma_px"            type="double"   value="1" />
+        <param name="up_aruco_chi2_multipler"      type="double"   value="1" />
+        <param name="gyroscope_noise_density"      type="double"   value="0.01" />
+        <param name="gyroscope_random_walk"        type="double"   value="0.0001" />
+        <param name="accelerometer_noise_density"  type="double"   value="0.1" />
+        <param name="accelerometer_random_walk"    type="double"   value="0.001" />
+
+        <!-- camera intrinsics -->
+        <rosparam param="cam0_wh">[640, 480]</rosparam>
+        <rosparam param="cam1_wh">[640, 480]</rosparam>
+        <param name="cam0_is_fisheye" type="bool" value="false" />
+        <param name="cam1_is_fisheye" type="bool" value="false" />
+        <rosparam param="cam0_k">[391.117,394.147,319.642,224.178]</rosparam>
+        <rosparam param="cam0_d">[0.00675,-0.00562,0.03121,-0.00828]</rosparam>
+        <rosparam param="cam1_k">[380.95187095303424, 380.3065956074995, 324.0678433553536, 225.9586983198407]</rosparam>
+        <rosparam param="cam1_d">[0.007044055287844759, -0.010251485722185347, 0.0006674304399871926, 0.001678899816379666]</rosparam>
+
+        <!-- camera extrinsics -->
+        <rosparam param="T_C0toI">
+            [
+            -0.0403012399974094,0.026311325355147,0.998841090570831,0.138044476707325,
+            -0.998999875552468,-0.0204364996635247,-0.0397693113802049,0.0148148255449128,
+            0.0193664323204907,-0.999444877739417,0.027108627033059,-0.0349149420753215,
+            0,0,0,1
+            ]
+        </rosparam>
+        <rosparam param="T_C1toI">
+            [
+            -0.0390575247256606,0.025035478432625,0.99892328763622,0.136237639761255,
+            -0.999049856889956,-0.0203233966663709,-0.0385531191487784,-0.0351047099443363,
+            0.0193363184309466,-0.999479956961414,0.0258054727130918,-0.0340043702351212,
+            0,0,0,1
+            ]
+        </rosparam>
+
+    </node>
+
+
+    <!-- play the dataset -->
+    <node pkg="rosbag" type="play" name="rosbag" args="-d 1 -s $(arg bag_start) $(arg bag)" required="true"/>
+
+    <!-- path viz of aligned gt -->
+    <node name="live_align_trajectory" pkg="ov_eval" type="live_align_trajectory" output="log" clear_params="true">
+        <param name="alignment_type" type="str" value="posyaw" />
+        <param name="path_gt"        type="str" value="$(arg bag_gt)" />
+    </node>
+
+    <!-- record the trajectory if enabled -->
+    <group if="$(arg dosave)">
+        <node name="recorder_estimate" pkg="ov_eval" type="pose_to_file" output="screen" required="true">
+            <param name="topic"      type="str" value="/ov_msckf/poseimu" />
+            <param name="topic_type" type="str" value="PoseWithCovarianceStamped" />
+            <param name="output"     type="str" value="$(arg path_est)" />
+        </node>
+    </group>
+
+<!--    &lt;!&ndash; record the groundtruth if enabled &ndash;&gt;-->
+<!--    <node name="gt" pkg="ov_eval" type="pose_to_file" output="screen" required="true">-->
+<!--        <param name="topic"      type="str" value="/pose_transformed" />-->
+<!--        <param name="topic_type" type="str" value="PoseStamped" />-->
+<!--        <param name="output"     type="str" value="$(arg bag_gt)" />-->
+<!--    </node>-->
+
+</launch>
\ No newline at end of file
diff --git a/ov_msckf/launch/pgeneva_ros_tum.launch b/ov_msckf/launch/pgeneva_ros_tum.launch
index d31653ef8..31b6a55c6 100644
--- a/ov_msckf/launch/pgeneva_ros_tum.launch
+++ b/ov_msckf/launch/pgeneva_ros_tum.launch
@@ -4,7 +4,9 @@
     <arg name="max_cameras" default="1" />
     <arg name="use_stereo"  default="true" />
     <arg name="bag_start"   default="0" />
-    <arg name="bag"         default="/home/patrick/datasets/tum/dataset-room1_512_16.bag" />
+    <arg name="dataset"     default="dataset-room1_512_16" /> <!-- dataset-room1_512_16, dataset-room3_512_16 -->
+    <arg name="bag"         default="/home/patrick/datasets/tum/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/tum_vi/$(arg dataset).csv" />
 
     <!-- imu starting thresholds -->
     <arg name="init_window_time"  default="1.0" />
@@ -23,7 +25,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- world/filter parameters -->
         <param name="use_fej"                type="bool"   value="true" />
@@ -61,6 +62,12 @@
         <param name="knn_ratio"          type="double" value="0.65" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
+
+        <!-- tracking mask -->
+        <param name="use_mask"           type="bool"   value="true" />
+        <param name="mask0"              type="string" value="$(find ov_data)/masks/tumvi0.png" />
+        <param name="mask1"              type="string" value="$(find ov_data)/masks/tumvi1.png" />
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="false" />
@@ -114,6 +121,12 @@
     <!-- play the dataset -->
     <node pkg="rosbag" type="play" name="rosbag" args="-d 1 -s $(arg bag_start) $(arg bag)" required="true"/>
 
+    <!-- path viz of aligned gt -->
+    <node name="live_align_trajectory" pkg="ov_eval" type="live_align_trajectory" output="log" clear_params="true">
+        <param name="alignment_type" type="str" value="posyaw" />
+        <param name="path_gt"        type="str" value="$(arg bag_gt)" />
+    </node>
+
     <!-- record the trajectory if enabled -->
     <group if="$(arg dosave)">
         <node name="recorder_estimate" pkg="ov_eval" type="pose_to_file" output="screen">
diff --git a/ov_msckf/launch/pgeneva_ros_uzhfpv.launch b/ov_msckf/launch/pgeneva_ros_uzhfpv.launch
index 6188cd9ea..cf91ca664 100644
--- a/ov_msckf/launch/pgeneva_ros_uzhfpv.launch
+++ b/ov_msckf/launch/pgeneva_ros_uzhfpv.launch
@@ -2,10 +2,12 @@
 
     <!-- mono or stereo and what ros bag to play -->
     <arg name="max_cameras" default="1" />
-    <arg name="use_stereo"  default="false" />
+    <arg name="use_stereo"  default="true" />
     <arg name="bag_start"   default="0" />
     <arg name="bag_durr"    default="999999" />
-    <arg name="bag"         default="/media/patrick/RPNG\ FLASH\ 2/uzhfpv_newer/indoor_45_2_snapdragon_with_gt.bag" />
+    <arg name="dataset"     default="indoor_45_4_snapdragon_with_gt" /> <!-- indoor_45_2_snapdragon_with_gt, indoor_45_4_snapdragon_with_gt -->
+    <arg name="bag"         default="/media/patrick/RPNG\ FLASH\ 2/uzhfpv_newer/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/uzh_fpv/$(arg dataset).txt" />
 
     <!-- what configuration mode we are in  -->
     <!-- 0: indoor forward facing  -->
@@ -33,7 +35,6 @@
         <param name="topic_imu"      type="string" value="/snappy_imu" />
         <param name="topic_camera0"  type="string" value="/snappy_cam/stereo_l" />
         <param name="topic_camera1"  type="string" value="/snappy_cam/stereo_r" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- world/filter parameters -->
         <param name="use_fej"                type="bool"   value="true" />
@@ -80,6 +81,7 @@
         <param name="knn_ratio"          type="double" value="0.65" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="false" />
@@ -203,6 +205,12 @@
     <!-- play the dataset -->
     <node pkg="rosbag" type="play" name="rosbag" args="-d 1 -s $(arg bag_start) -u $(arg bag_durr) $(arg bag)" required="true"/>
 
+    <!-- path viz of aligned gt -->
+    <node name="live_align_trajectory" pkg="ov_eval" type="live_align_trajectory" output="log" clear_params="true">
+        <param name="alignment_type" type="str" value="posyaw" />
+        <param name="path_gt"        type="str" value="$(arg bag_gt)" />
+    </node>
+
     <!-- record the trajectory if enabled -->
     <group if="$(arg dosave)">
         <node name="recorder_estimate" pkg="ov_eval" type="pose_to_file" output="screen">
diff --git a/ov_msckf/launch/pgeneva_serial_aruco.launch b/ov_msckf/launch/pgeneva_serial_aruco.launch
index 421aa6d1b..ddc5907bb 100644
--- a/ov_msckf/launch/pgeneva_serial_aruco.launch
+++ b/ov_msckf/launch/pgeneva_serial_aruco.launch
@@ -9,7 +9,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- bag parameters -->
 <!--        <param name="path_bag"    type="string" value="/home/patrick/datasets/vi_sensor/aruco_room/aruco_hallway_01.bag" />-->
@@ -55,6 +54,7 @@
         <param name="knn_ratio"          type="double" value="0.85" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="true" />
diff --git a/ov_msckf/launch/pgeneva_serial_eth.launch b/ov_msckf/launch/pgeneva_serial_eth.launch
index 86fc5a394..eb34b980c 100644
--- a/ov_msckf/launch/pgeneva_serial_eth.launch
+++ b/ov_msckf/launch/pgeneva_serial_eth.launch
@@ -4,9 +4,10 @@
     <!-- mono or stereo and what ros bag to play -->
     <arg name="max_cameras" default="2" />
     <arg name="use_stereo"  default="true" />
-    <arg name="bag_start"   default="7" /> <!-- v1-2: 0, mh1: 40, mh2: 35, mh3: 17.5, mh4-5: 15 -->
-    <arg name="bag"         default="/home/patrick/datasets/eth/V1_01_easy.bag" />
-    <arg name="bag_gt"      default="$(find ov_data)/euroc_mav/V1_01_easy.csv" /> <!-- $(find ov_data)/euroc_mav/V1_01_easy.csv -->
+    <arg name="dataset"     default="V1_02_medium" /> <!-- V1_01_easy, V1_02_medium, V2_02_medium -->
+    <arg name="bag_start"   default="0" /> <!-- v1-2: 0, mh1: 40, mh2: 35, mh3: 17.5, mh4-5: 15 -->
+    <arg name="bag"         default="/home/patrick/datasets/eth/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/euroc_mav/$(arg dataset).csv" />
 
     <!-- imu starting thresholds -->
     <arg name="init_window_time"  default="0.75" />
@@ -22,7 +23,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0,1]</rosparam>
 
         <!-- bag parameters -->
         <param name="path_bag"    type="string" value="$(arg bag)" />
@@ -75,6 +75,7 @@
         <param name="knn_ratio"          type="double" value="0.70" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="false" />
diff --git a/ov_msckf/launch/pgeneva_serial_ironsides.launch b/ov_msckf/launch/pgeneva_serial_ironsides.launch
index addfd6527..6041682fb 100644
--- a/ov_msckf/launch/pgeneva_serial_ironsides.launch
+++ b/ov_msckf/launch/pgeneva_serial_ironsides.launch
@@ -18,7 +18,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- bag parameters -->
         <param name="path_bag"    type="string" value="/home/patrick/datasets/ironsides/neighborhood_01.bag" /> <!-- neighborhood_01, neighborhood_02 -->
@@ -70,6 +69,12 @@
         <param name="knn_ratio"          type="double" value="0.65" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
+
+        <!-- tracking mask -->
+        <param name="use_mask"           type="bool"   value="true" />
+        <param name="mask0"              type="string" value="$(find ov_data)/masks/ironsides0.png" />
+        <param name="mask1"              type="string" value="$(find ov_data)/masks/ironsides1.png" />
 
         <param name="fi_max_dist"        type="double" value="100" />
         <param name="fi_max_baseline"    type="double" value="100" />
diff --git a/ov_msckf/launch/pgeneva_serial_tum.launch b/ov_msckf/launch/pgeneva_serial_tum.launch
index 15f6e60d1..0c980ecae 100644
--- a/ov_msckf/launch/pgeneva_serial_tum.launch
+++ b/ov_msckf/launch/pgeneva_serial_tum.launch
@@ -4,8 +4,9 @@
     <arg name="max_cameras" default="1" />
     <arg name="use_stereo"  default="true" />
     <arg name="bag_start"   default="4" />
-    <arg name="bag"         default="/home/patrick/datasets/tum/dataset-room1_512_16.bag" />
-    <arg name="bag_gt"      default="$(find ov_data)/tum_vi/dataset-room1_512_16.csv" /> <!-- $(find ov_data)/tum_vi/dataset-room1_512_16.csv -->
+    <arg name="dataset"     default="dataset-room1_512_16" /> <!-- dataset-room1_512_16, dataset-room3_512_16 -->
+    <arg name="bag"         default="/home/patrick/datasets/tum/$(arg dataset).bag" />
+    <arg name="bag_gt"      default="$(find ov_data)/tum_vi/$(arg dataset).csv" />
 
     <!-- imu starting thresholds -->
     <arg name="init_window_time"  default="1.0" />
@@ -19,7 +20,6 @@
         <param name="topic_imu"      type="string" value="/imu0" />
         <param name="topic_camera0"  type="string" value="/cam0/image_raw" />
         <param name="topic_camera1"  type="string" value="/cam1/image_raw" />
-        <rosparam param="stereo_pairs">[0, 1]</rosparam>
 
         <!-- bag parameters -->
         <param name="path_bag"    type="string" value="$(arg bag)" />
@@ -63,6 +63,12 @@
         <param name="knn_ratio"          type="double" value="0.65" />
         <param name="downsample_cameras" type="bool"   value="false" />
         <param name="multi_threading"    type="bool"   value="true" />
+        <param name="histogram_method"   type="string" value="HISTOGRAM" /> <!-- NONE, HISTOGRAM, CLAHE -->
+
+        <!-- tracking mask -->
+        <param name="use_mask"           type="bool"   value="true" />
+        <param name="mask0"              type="string" value="$(find ov_data)/masks/tumvi0.png" />
+        <param name="mask1"              type="string" value="$(find ov_data)/masks/tumvi1.png" />
 
         <!-- aruco tag/mapping properties -->
         <param name="use_aruco"        type="bool"   value="false" />
diff --git a/ov_msckf/launch/pgeneva_sim.launch b/ov_msckf/launch/pgeneva_sim.launch
index bd8394583..c61b13c4f 100644
--- a/ov_msckf/launch/pgeneva_sim.launch
+++ b/ov_msckf/launch/pgeneva_sim.launch
@@ -11,7 +11,7 @@
     <arg name="num_clones"  default="11" />
     <arg name="num_slam"    default="50" />
     <arg name="num_pts"     default="100" />
-    <arg name="max_cameras" default="1" />
+    <arg name="max_cameras" default="2" />
 
     <arg name="freq_cam"    default="10" />
     <arg name="freq_imu"    default="400" />
diff --git a/ov_msckf/scripts/run_ros_eth.sh b/ov_msckf/scripts/run_ros_eth.sh
index 74133a74b..fd7f1b7b6 100755
--- a/ov_msckf/scripts/run_ros_eth.sh
+++ b/ov_msckf/scripts/run_ros_eth.sh
@@ -62,7 +62,8 @@ imuthreshold=(
 )
 
 # location to save log files into
-save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_euroc/algorithms"
+save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_euroc/algorithms"
+save_path2="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_euroc/timings"
 bag_path="/media/patrick/RPNG\ FLASH\ 2/euroc"
 
 
@@ -82,7 +83,8 @@ for j in {00..04}; do
 
 # start timing
 start_time="$(date -u +%s)"
-filename_est="$save_path1/ov_2.3.1_${modes[h]}/${bagnames[i]}/${start_time}_estimate.txt"
+filename_est="$save_path1/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_estimate.txt"
+filename_time="$save_path2/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_timing.txt"
 
 # number of cameras
 if [ "${modes[h]}" == "mono" ]
@@ -109,7 +111,9 @@ roslaunch ov_msckf pgeneva_ros_eth.launch \
   bag_start:="${bagstarttimes[i]}" \
   init_imu_thresh:="${imuthreshold[i]}" \
   dosave:="true" \
-  path_est:="$filename_est" &> /dev/null
+  path_est:="$filename_est" \
+  dotime:="true" \
+  path_time:="$filename_time" &> /dev/null
 
 # print out the time elapsed
 end_time="$(date -u +%s)"
diff --git a/ov_msckf/scripts/run_ros_kaistvio.sh b/ov_msckf/scripts/run_ros_kaistvio.sh
new file mode 100755
index 000000000..76c50164a
--- /dev/null
+++ b/ov_msckf/scripts/run_ros_kaistvio.sh
@@ -0,0 +1,116 @@
+#!/usr/bin/env bash
+
+# Source our workspace directory to load ENV variables
+source /home/patrick/workspace/catkin_ws_ov/devel/setup.bash
+
+
+#=============================================================
+#=============================================================
+#=============================================================
+
+
+# estimator configurations
+modes=(
+    "mono"
+    "binocular"
+    "stereo"
+)
+
+# dataset locations
+bagnames=(
+    "circle"
+    "circle_fast"
+    "circle_head"
+    "infinite"
+    "infinite_fast"
+    "infinite_head"
+    "rotation"
+    "rotation_fast"
+    "square"
+    "square_fast"
+    "square_head"
+)
+
+# how far we should start into the dataset
+# this can be used to skip the initial sections
+bagstarttimes=(
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+    "0"
+)
+
+
+
+# location to save log files into
+save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_kaistvio/algorithms"
+save_path2="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_kaistvio/timings"
+bag_path="/media/patrick/RPNG\ FLASH\ 3/KAIST_VIO"
+
+#=============================================================
+#=============================================================
+#=============================================================
+
+
+# Loop through all modes
+for h in "${!modes[@]}"; do
+# Loop through all datasets
+for i in "${!bagnames[@]}"; do
+
+# Monte Carlo runs for this dataset
+# If you want more runs, change the below loop
+for j in {00..04}; do
+
+# start timing
+start_time="$(date -u +%s)"
+filename_est="$save_path1/ov_2.3.3_${modes[h]}/${bagnames[i]}/${j}_estimate.txt"
+filename_time="$save_path2/ov_2.3.3_${modes[h]}/${bagnames[i]}/${j}_timing.txt"
+
+# number of cameras
+if [ "${modes[h]}" == "mono" ]
+then
+  temp1="1"
+  temp2="true"
+fi
+if [ "${modes[h]}" == "binocular" ]
+then
+  temp1="2"
+  temp2="false"
+fi
+if [ "${modes[h]}" == "stereo" ]
+then
+  temp1="2"
+  temp2="true"
+fi
+
+# run our ROS launch file (note we send console output to terminator)
+roslaunch ov_msckf pgeneva_ros_kaistvio.launch \
+  max_cameras:="$temp1" \
+  use_stereo:="$temp2" \
+  bag:="$bag_path/${bagnames[i]}.bag" \
+  bag_start:="${bagstarttimes[i]}" \
+  dosave:="true" \
+  path_est:="$filename_est" \
+  dotime:="true" \
+  path_time:="$filename_time" &> /dev/null
+
+
+# print out the time elapsed
+end_time="$(date -u +%s)"
+elapsed="$(($end_time-$start_time))"
+echo "BASH: ${modes[h]} - ${bagnames[i]} - run $j took $elapsed seconds";
+
+done
+
+
+done
+done
+
+
diff --git a/ov_msckf/scripts/run_ros_tumvi.sh b/ov_msckf/scripts/run_ros_tumvi.sh
index 4b795153a..9c9130086 100755
--- a/ov_msckf/scripts/run_ros_tumvi.sh
+++ b/ov_msckf/scripts/run_ros_tumvi.sh
@@ -49,7 +49,8 @@ imuthreshold=(
 )
 
 # location to save log files into
-save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_tum/algorithms"
+save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_tum/algorithms"
+save_path2="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_tum/timings"
 bag_path="/media/patrick/RPNG\ FLASH\ 2/tumvi"
 
 
@@ -69,7 +70,8 @@ for j in {00..04}; do
 
 # start timing
 start_time="$(date -u +%s)"
-filename_est="$save_path1/ov_2.3.1_${modes[h]}/${bagnames[i]}/${start_time}_estimate.txt"
+filename_est="$save_path1/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_estimate.txt"
+filename_time="$save_path2/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_timing.txt"
 
 # number of cameras
 if [ "${modes[h]}" == "mono" ]
@@ -96,7 +98,9 @@ roslaunch ov_msckf pgeneva_ros_tum.launch \
   bag_start:="${bagstarttimes[i]}" \
   init_imu_thresh:="${imuthreshold[i]}" \
   dosave:="true" \
-  path_est:="$filename_est" &> /dev/null
+  path_est:="$filename_est" \
+  dotime:="true" \
+  path_time:="$filename_time" &> /dev/null
 
 # print out the time elapsed
 end_time="$(date -u +%s)"
diff --git a/ov_msckf/scripts/run_ros_uzhfpv.sh b/ov_msckf/scripts/run_ros_uzhfpv.sh
index d6bc088a4..bec63d591 100755
--- a/ov_msckf/scripts/run_ros_uzhfpv.sh
+++ b/ov_msckf/scripts/run_ros_uzhfpv.sh
@@ -111,8 +111,8 @@ imuthreshold=(
 )
 
 # location to save log files into
-save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_uzhfpv/algorithms"
-save_path2="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.3.1/exp_uzhfpv/timings"
+save_path1="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_uzhfpv/algorithms"
+save_path2="/home/patrick/github/pubs_data/pgeneva/2020_openvins_2.4/exp_uzhfpv/timings"
 bag_path="/media/patrick/RPNG\ FLASH\ 2/uzhfpv_newer"
 
 #=============================================================
@@ -131,8 +131,8 @@ for j in {00..04}; do
 
 # start timing
 start_time="$(date -u +%s)"
-filename_est="$save_path1/ov_2.3.1_${modes[h]}/${bagnames[i]}/${j}_estimate.txt"
-filename_time="$save_path2/ov_2.3.1_${modes[h]}/${bagnames[i]}/${j}_timing.txt"
+filename_est="$save_path1/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_estimate.txt"
+filename_time="$save_path2/ov_2.4_${modes[h]}/${bagnames[i]}/${j}_timing.txt"
 
 # number of cameras
 if [ "${modes[h]}" == "mono" ]
diff --git a/ov_msckf/src/core/RosVisualizer.cpp b/ov_msckf/src/core/RosVisualizer.cpp
index ab41a1497..e13524aad 100644
--- a/ov_msckf/src/core/RosVisualizer.cpp
+++ b/ov_msckf/src/core/RosVisualizer.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "RosVisualizer.h"
 
 using namespace ov_msckf;
@@ -73,7 +72,10 @@ RosVisualizer::RosVisualizer(ros::NodeHandle &nh, std::shared_ptr<VioManager> ap
   if (nh.hasParam("path_gt") && _sim == nullptr) {
     std::string path_to_gt;
     nh.param<std::string>("path_gt", path_to_gt, "");
-    DatasetReader::load_gt_file(path_to_gt, gt_states);
+    if(!path_to_gt.empty()) {
+      DatasetReader::load_gt_file(path_to_gt, gt_states);
+      ROS_INFO("gt file path is: %s", path_to_gt.c_str());
+    }
   }
 
   // Load if we should save the total state to file
@@ -656,11 +658,13 @@ void RosVisualizer::publish_groundtruth() {
   //==========================================================================
 
   // Update our average variables
-  summed_rmse_ori += rmse_ori;
-  summed_rmse_pos += rmse_pos;
-  summed_nees_ori += ori_nees;
-  summed_nees_pos += pos_nees;
-  summed_number++;
+  if (!std::isnan(ori_nees) && !std::isnan(pos_nees)) {
+    summed_rmse_ori += rmse_ori;
+    summed_rmse_pos += rmse_pos;
+    summed_nees_ori += ori_nees;
+    summed_nees_pos += pos_nees;
+    summed_number++;
+  }
 
   // Nice display for the user
   printf(REDPURPLE "error to gt => %.3f, %.3f (deg,m) | average error => %.3f, %.3f (deg,m) | called %d times\n" RESET, rmse_ori, rmse_pos,
@@ -731,7 +735,7 @@ void RosVisualizer::publish_loopclosure_information() {
     sensor_msgs::CameraInfo cameraparams;
     cameraparams.header = header;
     cameraparams.header.frame_id = "imu";
-    cameraparams.distortion_model = (_app->get_state()->_cam_intrinsics_model.at(0)) ? "equidistant" : "plumb_bob";
+    cameraparams.distortion_model = (_app->get_params().camera_fisheye.at(0)) ? "equidistant" : "plumb_bob";
     Eigen::VectorXd cparams = _app->get_state()->_cam_intrinsics.at(0)->value();
     cameraparams.D = {cparams(4), cparams(5), cparams(6), cparams(7)};
     cameraparams.K = {cparams(0), 0, cparams(2), 0, cparams(1), cparams(3), 0, 0, 1};
diff --git a/ov_msckf/src/core/RosVisualizer.h b/ov_msckf/src/core/RosVisualizer.h
index 122806f43..706122655 100644
--- a/ov_msckf/src/core/RosVisualizer.h
+++ b/ov_msckf/src/core/RosVisualizer.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_ROSVISUALIZER_H
 #define OV_MSCKF_ROSVISUALIZER_H
 
diff --git a/ov_msckf/src/core/VioManager.cpp b/ov_msckf/src/core/VioManager.cpp
index 62160fa1f..f3c2a202c 100644
--- a/ov_msckf/src/core/VioManager.cpp
+++ b/ov_msckf/src/core/VioManager.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "VioManager.h"
 
 #include "types/Landmark.h"
@@ -61,8 +60,14 @@ VioManager::VioManager(VioManagerOptions &params_) {
   // Loop through through, and load each of the cameras
   for (int i = 0; i < state->_options.num_cameras; i++) {
 
-    // If our distortions are fisheye or not!
-    state->_cam_intrinsics_model.at(i) = params.camera_fisheye.at(i);
+    // Create the actual camera object and set the values
+    if (params.camera_fisheye.at(i)) {
+      state->_cam_intrinsics_cameras.insert({i, std::make_shared<CamEqui>()});
+      state->_cam_intrinsics_cameras.at(i)->set_value(params.camera_intrinsics.at(i));
+    } else {
+      state->_cam_intrinsics_cameras.insert({i, std::make_shared<CamRadtan>()});
+      state->_cam_intrinsics_cameras.at(i)->set_value(params.camera_intrinsics.at(i));
+    }
 
     // Camera intrinsic properties
     state->_cam_intrinsics.at(i)->set_value(params.camera_intrinsics.at(i));
@@ -104,19 +109,19 @@ VioManager::VioManager(VioManagerOptions &params_) {
   // Lets make a feature extractor
   trackDATABASE = std::make_shared<FeatureDatabase>();
   if (params.use_klt) {
-    trackFEATS = std::shared_ptr<TrackBase>(new TrackKLT(params.num_pts, state->_options.max_aruco_features, params.fast_threshold,
-                                                         params.grid_x, params.grid_y, params.min_px_dist));
-    trackFEATS->set_calibration(params.camera_intrinsics, params.camera_fisheye);
+    trackFEATS = std::shared_ptr<TrackBase>(new TrackKLT(state->_cam_intrinsics_cameras, params.num_pts, state->_options.max_aruco_features,
+                                                         params.use_stereo, params.histogram_method, params.fast_threshold, params.grid_x,
+                                                         params.grid_y, params.min_px_dist));
   } else {
-    trackFEATS = std::shared_ptr<TrackBase>(new TrackDescriptor(params.num_pts, state->_options.max_aruco_features, params.fast_threshold,
-                                                                params.grid_x, params.grid_y, params.knn_ratio));
-    trackFEATS->set_calibration(params.camera_intrinsics, params.camera_fisheye);
+    trackFEATS = std::shared_ptr<TrackBase>(new TrackDescriptor(
+        state->_cam_intrinsics_cameras, params.num_pts, state->_options.max_aruco_features, params.use_stereo, params.histogram_method,
+        params.fast_threshold, params.grid_x, params.grid_y, params.min_px_dist, params.knn_ratio));
   }
 
   // Initialize our aruco tag extractor
   if (params.use_aruco) {
-    trackARUCO = std::shared_ptr<TrackBase>(new TrackAruco(state->_options.max_aruco_features, params.downsize_aruco));
-    trackARUCO->set_calibration(params.camera_intrinsics, params.camera_fisheye);
+    trackARUCO = std::shared_ptr<TrackBase>(new TrackAruco(state->_cam_intrinsics_cameras, state->_options.max_aruco_features,
+                                                           params.use_stereo, params.histogram_method, params.downsize_aruco));
   }
 
   // Initialize our state propagator
@@ -131,8 +136,8 @@ VioManager::VioManager(VioManagerOptions &params_) {
 
   // If we are using zero velocity updates, then create the updater
   if (params.try_zupt) {
-    updaterZUPT = std::make_shared<UpdaterZeroVelocity>(params.zupt_options, params.imu_noises, trackFEATS->get_feature_database(), propagator,
-                                                        params.gravity_mag, params.zupt_max_velocity,
+    updaterZUPT = std::make_shared<UpdaterZeroVelocity>(params.zupt_options, params.imu_noises, trackFEATS->get_feature_database(),
+                                                        propagator, params.gravity_mag, params.zupt_max_velocity,
                                                         params.zupt_noise_multiplier, params.zupt_max_disparity);
   }
 
@@ -164,10 +169,9 @@ void VioManager::feed_measurement_imu(const ov_core::ImuData &message) {
   }
 
   // If we do not have enough unique cameras then we need to wait
-  // This is since we will not be sure if the missing unique cameras will need to be propagated to first
-  // The issue here is that if we have a slow frame-rate camera this will cause lag...
-  // Another way is to try to "predict" if the missing images will come in after the current oldest frame
-  if ((int)unique_cam_ids.size() != params.state_options.num_unique_cameras)
+  // We should wait till we have one of each camera to ensure we propagate in the correct order
+  size_t num_unique_cameras = (params.state_options.num_cameras == 2) ? 1 : params.state_options.num_cameras;
+  if (unique_cam_ids.size() != num_unique_cameras)
     return;
 
   // Loop through our queue and see if we are able to process any of our camera measurements
@@ -190,9 +194,8 @@ void VioManager::feed_measurement_simulation(double timestamp, const std::vector
   std::shared_ptr<TrackSIM> trackSIM = dynamic_pointer_cast<TrackSIM>(trackFEATS);
   if (trackSIM == nullptr) {
     // Replace with the simulated tracker
-    trackSIM = std::make_shared<TrackSIM>(state->_options.max_aruco_features);
+    trackSIM = std::make_shared<TrackSIM>(state->_cam_intrinsics_cameras, state->_options.max_aruco_features);
     trackFEATS = trackSIM;
-    trackFEATS->set_calibration(params.camera_intrinsics, params.camera_fisheye);
     printf(RED "[SIM]: casting our tracker to a TrackSIM object!\n" RESET);
   }
   trackSIM->set_width_height(params.camera_wh);
@@ -248,8 +251,9 @@ void VioManager::feed_measurement_simulation(double timestamp, const std::vector
   message.timestamp = timestamp;
   for (auto const &camid : camids) {
     auto &wh = params.camera_wh.at(camid);
-    message.images.push_back(cv::Mat::zeros(cv::Size(wh.first, wh.second), CV_8UC1));
     message.sensor_ids.push_back(camid);
+    message.images.push_back(cv::Mat::zeros(cv::Size(wh.first, wh.second), CV_8UC1));
+    message.masks.push_back(cv::Mat::zeros(cv::Size(wh.first, wh.second), CV_8UC1));
   }
   do_feature_propagate_update(message);
 }
@@ -260,7 +264,6 @@ void VioManager::track_image_and_update(const ov_core::CameraData &message_const
   rT1 = boost::posix_time::microsec_clock::local_time();
 
   // Assert we have valid measurement data and ids
-  int num_images = (int)message_const.sensor_ids.size();
   assert(!message_const.sensor_ids.empty());
   assert(message_const.sensor_ids.size() == message_const.images.size());
   for (size_t i = 0; i < message_const.sensor_ids.size() - 1; i++) {
@@ -281,41 +284,15 @@ void VioManager::track_image_and_update(const ov_core::CameraData &message_const
     zupt_img_last[message.sensor_ids.at(i)] = message.images.at(i).clone();
   }
 
-  // Perform our feature tracking
-  //  1) single cameras we are monocular
-  //  2) two cameras we are stereo
-  if (num_images == 1) {
-    trackFEATS->feed_monocular(message.timestamp, message.images.at(0), message.sensor_ids.at(0));
-  } else if (num_images == 2) {
-    if (params.use_stereo) {
-      trackFEATS->feed_stereo(message.timestamp, message.images.at(0), message.images.at(1), message.sensor_ids.at(0),
-                              message.sensor_ids.at(1));
-    } else {
-      parallel_for_(cv::Range(0, 2), LambdaBody([&](const cv::Range &range) {
-                      for (int i = range.start; i < range.end; i++) {
-                        trackFEATS->feed_monocular(message.timestamp, message.images.at(i), message.sensor_ids.at(i));
-                      }
-                    }));
-    }
-  } else {
-    printf(RED "invalid number of images passed %d, we only support mono or stereo tracking", num_images);
-    std::exit(EXIT_FAILURE);
-  }
+  // Perform our feature tracking!
+  trackFEATS->feed_new_camera(message);
   trackDATABASE->append_new_measurements(trackFEATS->get_feature_database());
 
   // If the aruco tracker is available, the also pass to it
   // NOTE: binocular tracking for aruco doesn't make sense as we by default have the ids
   // NOTE: thus we just call the stereo tracking if we are doing binocular!
   if (trackARUCO != nullptr) {
-    if (num_images == 1) {
-      trackARUCO->feed_monocular(message.timestamp, message.images.at(0), message.sensor_ids.at(0));
-    } else if (num_images == 2) {
-      trackARUCO->feed_stereo(message.timestamp, message.images.at(0), message.images.at(1), message.sensor_ids.at(0),
-                              message.sensor_ids.at(1));
-    } else {
-      printf(RED "invalid number of images passed %d, we only support mono or stereo tracking", num_images);
-      std::exit(EXIT_FAILURE);
-    }
+    trackARUCO->feed_new_camera(message);
     trackDATABASE->append_new_measurements(trackARUCO->get_feature_database());
   }
   rT2 = boost::posix_time::microsec_clock::local_time();
@@ -593,26 +570,6 @@ void VioManager::do_feature_propagate_update(const ov_core::CameraData &message)
   // Update our visualization feature set, and clean up the old features
   //===================================================================================
 
-  // Finally if we are optimizing our intrinsics, update our trackers
-  // TODO: we shouldn't need to do this, in the future just do this before triangulation etc.
-  // TODO: this is the best we can do right now since triangulation & ransac need normalized coordinates
-  if (state->_options.do_calib_camera_intrinsics) {
-    // Get vectors arrays
-    std::map<size_t, Eigen::VectorXd> cameranew_calib;
-    std::map<size_t, bool> cameranew_fisheye;
-    for (int i = 0; i < state->_options.num_cameras; i++) {
-      std::shared_ptr<Vec> calib = state->_cam_intrinsics.at(i);
-      bool isfish = state->_cam_intrinsics_model.at(i);
-      cameranew_calib.insert({i, calib->value()});
-      cameranew_fisheye.insert({i, isfish});
-    }
-    // Update the trackers and their databases
-    trackFEATS->set_calibration(cameranew_calib, cameranew_fisheye, false);
-    if (trackARUCO != nullptr) {
-      trackARUCO->set_calibration(cameranew_calib, cameranew_fisheye, false);
-    }
-  }
-
   // Re-triangulate all current tracks in the current frame
   if (message.sensor_ids.at(0) == 0) {
 
@@ -838,7 +795,7 @@ void VioManager::retriangulate_active_tracks(const ov_core::CameraData &message)
     }
 
     // Remove if we don't have enough and am not a SLAM feature which doesn't need triangulation
-    if (ct_meas < (int)std::max(0.0, std::floor(state->_options.max_clone_size * 2.0 / 5.0))) {
+    if (ct_meas < (int)std::max(4.0, std::floor(state->_options.max_clone_size * 2.0 / 5.0))) {
       it0 = active_features.erase(it0);
     } else {
       it0++;
@@ -859,8 +816,8 @@ void VioManager::retriangulate_active_tracks(const ov_core::CameraData &message)
     for (const auto &clone_imu : state->_clones_IMU) {
 
       // Get current camera pose
-      Eigen::Matrix<double, 3, 3> R_GtoCi = clone_calib.second->Rot() * clone_imu.second->Rot();
-      Eigen::Matrix<double, 3, 1> p_CioinG = clone_imu.second->pos() - R_GtoCi.transpose() * clone_calib.second->pos();
+      Eigen::Matrix3d R_GtoCi = clone_calib.second->Rot() * clone_imu.second->Rot();
+      Eigen::Vector3d p_CioinG = clone_imu.second->pos() - R_GtoCi.transpose() * clone_calib.second->pos();
 
       // Append to our map
       clones_cami.insert({clone_imu.first, FeatureInitializer::ClonePose(R_GtoCi, p_CioinG)});
@@ -906,11 +863,11 @@ void VioManager::retriangulate_active_tracks(const ov_core::CameraData &message)
       // Assert that we have an anchor pose for this feature
       assert(feat.second->_anchor_cam_id != -1);
       // Get calibration for our anchor camera
-      Eigen::Matrix<double, 3, 3> R_ItoC = state->_calib_IMUtoCAM.at(feat.second->_anchor_cam_id)->Rot();
-      Eigen::Matrix<double, 3, 1> p_IinC = state->_calib_IMUtoCAM.at(feat.second->_anchor_cam_id)->pos();
+      Eigen::Matrix3d R_ItoC = state->_calib_IMUtoCAM.at(feat.second->_anchor_cam_id)->Rot();
+      Eigen::Vector3d p_IinC = state->_calib_IMUtoCAM.at(feat.second->_anchor_cam_id)->pos();
       // Anchor pose orientation and position
-      Eigen::Matrix<double, 3, 3> R_GtoI = state->_clones_IMU.at(feat.second->_anchor_clone_timestamp)->Rot();
-      Eigen::Matrix<double, 3, 1> p_IinG = state->_clones_IMU.at(feat.second->_anchor_clone_timestamp)->pos();
+      Eigen::Matrix3d R_GtoI = state->_clones_IMU.at(feat.second->_anchor_clone_timestamp)->Rot();
+      Eigen::Vector3d p_IinG = state->_clones_IMU.at(feat.second->_anchor_clone_timestamp)->pos();
       // Feature in the global frame
       p_FinG = R_GtoI.transpose() * R_ItoC.transpose() * (feat.second->get_xyz(false) - p_IinC) + p_IinG;
     }
@@ -922,7 +879,6 @@ void VioManager::retriangulate_active_tracks(const ov_core::CameraData &message)
   std::shared_ptr<PoseJPL> calibration = state->_calib_IMUtoCAM.at(0);
   Eigen::Matrix<double, 3, 3> R_ItoC = calibration->Rot();
   Eigen::Matrix<double, 3, 1> p_IinC = calibration->pos();
-  Eigen::Matrix<double, 8, 1> cam_d = distortion->value();
 
   // Get current IMU clone state
   std::shared_ptr<PoseJPL> clone_Ii = state->_clones_IMU.at(active_tracks_time);
@@ -939,42 +895,16 @@ void VioManager::retriangulate_active_tracks(const ov_core::CameraData &message)
     double depth = p_FinCi(2);
     Eigen::Vector2d uv_norm, uv_dist;
     uv_norm << p_FinCi(0) / depth, p_FinCi(1) / depth;
+    uv_dist = state->_cam_intrinsics_cameras.at(0)->distort_d(uv_norm);
 
     // Skip if not valid (i.e. negative depth, or outside of image)
     if (depth < 0.1) {
       continue;
     }
 
-    // Calculate distorted uv coordinate
-    //  1. Calculate distorted coordinates for fisheye
-    //  2. Calculate distorted coordinates for radial
-    if (state->_cam_intrinsics_model.at(0)) {
-      double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-      double theta = std::atan(r);
-      double theta_d = theta + cam_d(4) * std::pow(theta, 3) + cam_d(5) * std::pow(theta, 5) + cam_d(6) * std::pow(theta, 7) +
-                       cam_d(7) * std::pow(theta, 9);
-      // Handle when r is small (meaning our xy is near the camera center)
-      double inv_r = (r > 1e-8) ? 1.0 / r : 1.0;
-      double cdist = (r > 1e-8) ? theta_d * inv_r : 1.0;
-      // Calculate distorted coordinates for fisheye
-      double x1 = uv_norm(0) * cdist;
-      double y1 = uv_norm(1) * cdist;
-      uv_dist(0) = cam_d(0) * x1 + cam_d(2);
-      uv_dist(1) = cam_d(1) * y1 + cam_d(3);
-    } else {
-      double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-      double r_2 = r * r;
-      double r_4 = r_2 * r_2;
-      double x1 = uv_norm(0) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + 2 * cam_d(6) * uv_norm(0) * uv_norm(1) +
-                  cam_d(7) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
-      double y1 = uv_norm(1) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + cam_d(6) * (r_2 + 2 * uv_norm(1) * uv_norm(1)) +
-                  2 * cam_d(7) * uv_norm(0) * uv_norm(1);
-      uv_dist(0) = cam_d(0) * x1 + cam_d(2);
-      uv_dist(1) = cam_d(1) * y1 + cam_d(3);
-    }
-
     // Skip if not valid (i.e. negative depth, or outside of image)
-    if (uv_dist(0) < 0 || uv_dist(0) > params.camera_wh.at(0).first || uv_dist(1) < 0 || uv_dist(1) > params.camera_wh.at(0).second) {
+    if (uv_dist(0) < 0 || (int)uv_dist(0) >= params.camera_wh.at(0).first || uv_dist(1) < 0 ||
+        (int)uv_dist(1) >= params.camera_wh.at(0).second) {
       // printf("feat %zu -> depth = %.2f | u_d = %.2f | v_d = %.2f\n",(*it2)->featid,depth,uv_dist(0),uv_dist(1));
       continue;
     }
diff --git a/ov_msckf/src/core/VioManager.h b/ov_msckf/src/core/VioManager.h
index d882e7503..43702c9d9 100644
--- a/ov_msckf/src/core/VioManager.h
+++ b/ov_msckf/src/core/VioManager.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_VIOMANAGER_H
 #define OV_MSCKF_VIOMANAGER_H
 
@@ -30,6 +29,9 @@
 #include <memory>
 #include <string>
 
+#include "cam/CamBase.h"
+#include "cam/CamEqui.h"
+#include "cam/CamRadtan.h"
 #include "init/InertialInitializer.h"
 #include "track/TrackAruco.h"
 #include "track/TrackDescriptor.h"
diff --git a/ov_msckf/src/core/VioManagerOptions.h b/ov_msckf/src/core/VioManagerOptions.h
index ad6915396..70d336f0b 100644
--- a/ov_msckf/src/core/VioManagerOptions.h
+++ b/ov_msckf/src/core/VioManagerOptions.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_VIOMANAGEROPTIONS_H
 #define OV_MSCKF_VIOMANAGEROPTIONS_H
 
@@ -31,6 +30,7 @@
 #include "feat/FeatureInitializerOptions.h"
 #include "state/Propagator.h"
 #include "state/StateOptions.h"
+#include "track/TrackBase.h"
 #include "update/UpdaterOptions.h"
 #include "utils/colors.h"
 #include "utils/quat_ops.h"
@@ -186,9 +186,6 @@ struct VioManagerOptions {
   /// If we should process two cameras are being stereo or binocular. If binocular, we do monocular feature tracking on each image.
   bool use_stereo = true;
 
-  /// Defined set of stereo camera id pairs which we will process together and try to generate stereo constraints between.
-  std::vector<std::pair<int, int>> stereo_pairs;
-
   /// If we should use KLT tracking, or descriptor matcher
   bool use_klt = true;
 
@@ -219,9 +216,18 @@ struct VioManagerOptions {
   /// Will check after doing KLT track and remove any features closer than this
   int min_px_dist = 10;
 
+  /// What type of pre-processing histogram method should be applied to images
+  TrackBase::HistogramMethod histogram_method = TrackBase::HistogramMethod::HISTOGRAM;
+
   /// KNN ration between top two descriptor matcher which is required to be a good match
   double knn_ratio = 0.85;
 
+  /// If we should try to load a mask and use it to reject invalid features
+  bool use_mask = false;
+
+  /// Mask images for each camera
+  std::map<size_t, cv::Mat> masks;
+
   /// Parameters used by our feature initialize / triangulator
   FeatureInitializerOptions featinit_options;
 
@@ -230,16 +236,19 @@ struct VioManagerOptions {
    */
   void print_trackers() {
     printf("FEATURE TRACKING PARAMETERS:\n");
-    printf("\t- num_pts: %d\n", num_pts);
+    printf("\t- use_klt: %d\n", use_klt);
     printf("\t- use_stereo: %d\n", use_stereo);
-    printf("\t- stereo pairs: ");
-    for (const auto &pair : stereo_pairs) {
-      printf("[%d, %d] ", pair.first, pair.second);
-    }
-    printf("\n");
+    printf("\t- use_aruco: %d\n", use_aruco);
     printf("\t- downsize aruco: %d\n", downsize_aruco);
     printf("\t- downsize cameras: %d\n", downsample_cameras);
     printf("\t- use multi-threading: %d\n", use_multi_threading);
+    printf("\t- num_pts: %d\n", num_pts);
+    printf("\t- fast threshold: %d\n", fast_threshold);
+    printf("\t- grid X by Y: %d by %d\n", grid_x, grid_y);
+    printf("\t- min px dist: %d\n", min_px_dist);
+    printf("\t- hist method: %d\n", (int)histogram_method);
+    printf("\t- knn ratio: %.3f\n", knn_ratio);
+    printf("\t- use mask?: %d\n", use_mask);
     featinit_options.print();
   }
 
diff --git a/ov_msckf/src/dummy.cpp b/ov_msckf/src/dummy.cpp
index 3a3ea22ac..60eb052b5 100644
--- a/ov_msckf/src/dummy.cpp
+++ b/ov_msckf/src/dummy.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 /**
  * @namespace ov_msckf
  *
diff --git a/ov_msckf/src/ros_serial_msckf.cpp b/ov_msckf/src/ros_serial_msckf.cpp
index 91e1e56be..43753b619 100644
--- a/ov_msckf/src/ros_serial_msckf.cpp
+++ b/ov_msckf/src/ros_serial_msckf.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <cv_bridge/cv_bridge.h>
 #include <ros/ros.h>
 #include <rosbag/bag.h>
@@ -64,28 +62,23 @@ int main(int argc, char **argv) {
 
   // Our camera topics (stereo pairs and non-stereo mono)
   std::vector<std::pair<size_t, std::string>> topic_cameras;
-  std::vector<int> stereo_cam_ids;
-  for (const auto &pair : params.stereo_pairs) {
+  if (params.use_stereo && params.state_options.num_cameras == 2) {
     // Read in the topics
     std::string cam_topic0, cam_topic1;
-    nh.param<std::string>("topic_camera" + std::to_string(pair.first), cam_topic0, "/cam" + std::to_string(pair.first) + "/image_raw");
-    nh.param<std::string>("topic_camera" + std::to_string(pair.second), cam_topic1, "/cam" + std::to_string(pair.second) + "/image_raw");
-    topic_cameras.emplace_back(pair.first, cam_topic0);
-    topic_cameras.emplace_back(pair.second, cam_topic1);
-    stereo_cam_ids.push_back(pair.first);
-    stereo_cam_ids.push_back(pair.second);
+    nh.param<std::string>("topic_camera" + std::to_string(0), cam_topic0, "/cam" + std::to_string(0) + "/image_raw");
+    nh.param<std::string>("topic_camera" + std::to_string(1), cam_topic1, "/cam" + std::to_string(1) + "/image_raw");
+    topic_cameras.emplace_back(0, cam_topic0);
+    topic_cameras.emplace_back(1, cam_topic1);
     ROS_INFO("serial cam (stereo): %s", cam_topic0.c_str());
     ROS_INFO("serial cam (stereo): %s", cam_topic1.c_str());
-  }
-  for (int i = 0; i < params.state_options.num_cameras; i++) {
-    // Skip if already have been added
-    if (std::find(stereo_cam_ids.begin(), stereo_cam_ids.end(), i) != stereo_cam_ids.end())
-      continue;
-    // read in the topic
-    std::string cam_topic;
-    nh.param<std::string>("topic_camera" + std::to_string(i), cam_topic, "/cam" + std::to_string(i) + "/image_raw");
-    topic_cameras.emplace_back(i, cam_topic);
-    ROS_INFO("serial cam (mono): %s", cam_topic.c_str());
+  } else {
+    for (int i = 0; i < params.state_options.num_cameras; i++) {
+      // read in the topic
+      std::string cam_topic;
+      nh.param<std::string>("topic_camera" + std::to_string(i), cam_topic, "/cam" + std::to_string(i) + "/image_raw");
+      topic_cameras.emplace_back(i, cam_topic);
+      ROS_INFO("serial cam (mono): %s", cam_topic.c_str());
+    }
   }
 
   // Location of the ROS bag we want to read in
@@ -98,8 +91,10 @@ int main(int argc, char **argv) {
   if (nh.hasParam("path_gt")) {
     std::string path_to_gt;
     nh.param<std::string>("path_gt", path_to_gt, "");
-    DatasetReader::load_gt_file(path_to_gt, gt_states);
-    ROS_INFO("gt file path is: %s", path_to_gt.c_str());
+    if(!path_to_gt.empty()) {
+      DatasetReader::load_gt_file(path_to_gt, gt_states);
+      ROS_INFO("gt file path is: %s", path_to_gt.c_str());
+    }
   }
 
   // Get our start location and how much of the bag we want to play
@@ -110,10 +105,6 @@ int main(int argc, char **argv) {
   ROS_INFO("bag start: %.1f", bag_start);
   ROS_INFO("bag duration: %.1f", bag_durr);
 
-  // Read in what mode we should be processing in (1=mono, 2=stereo)
-  int max_cameras;
-  nh.param<int>("max_cameras", max_cameras, 1);
-
   //===================================================================================
   //===================================================================================
   //===================================================================================
@@ -144,98 +135,228 @@ int main(int argc, char **argv) {
     return EXIT_FAILURE;
   }
 
+  // Open our iterators
+  auto view_imu = std::make_shared<rosbag::View>(bag, rosbag::TopicQuery(topic_imu), time_init, time_finish);
+  auto view_imu_iter = view_imu->begin();
+  std::vector<std::shared_ptr<rosbag::View>> view_cameras;
+  std::vector<rosbag::View::iterator> view_cameras_iterators;
+  for (const auto &topic : topic_cameras) {
+    auto view_tmp = std::make_shared<rosbag::View>(bag, rosbag::TopicQuery(topic.second), time_init, time_finish);
+    view_cameras.push_back(view_tmp);
+    view_cameras_iterators.push_back(view_tmp->begin());
+  }
+
+  // Record the current measurement timestamps
+  sensor_msgs::Imu::ConstPtr msg_imu_current;
+  sensor_msgs::Imu::ConstPtr msg_imu_next;
+  std::vector<sensor_msgs::Image::ConstPtr> msg_images_current;
+  std::vector<sensor_msgs::Image::ConstPtr> msg_images_next;
+  msg_imu_current = view_imu_iter->instantiate<sensor_msgs::Imu>();
+  view_imu_iter++;
+  msg_imu_next = view_imu_iter->instantiate<sensor_msgs::Imu>();
+  for (int i = 0; i < params.state_options.num_cameras; i++) {
+    msg_images_current.emplace_back(view_cameras_iterators.at(i)->instantiate<sensor_msgs::Image>());
+    view_cameras_iterators.at(i)++;
+    msg_images_next.emplace_back(view_cameras_iterators.at(i)->instantiate<sensor_msgs::Image>());
+  }
+
   //===================================================================================
   //===================================================================================
   //===================================================================================
 
-  // Latest collection of image information
-  std::map<size_t, std::pair<double, cv::Mat>> image_buffer;
+  while (ros::ok()) {
 
-  // Step through the rosbag
-  for (const rosbag::MessageInstance &m : view) {
-
-    // If ros is wants us to stop, break out
-    if (!ros::ok())
+    // Check if we should end since we have run out of measurements
+    bool should_stop = false;
+    if (view_imu_iter == view_imu->end()) {
+      should_stop = true;
+    }
+    for (int i = 0; i < params.state_options.num_cameras; i++) {
+      if (view_cameras_iterators.at(i) == view_cameras.at(i)->end()) {
+        should_stop = true;
+      }
+    }
+    if (should_stop) {
       break;
+    }
 
-    // Handle IMU measurement
-    sensor_msgs::Imu::ConstPtr s2 = m.instantiate<sensor_msgs::Imu>();
-    if (s2 != nullptr && m.getTopic() == topic_imu) {
+    // We should process the IMU if all the current cameras are greater then its time
+    bool should_process_imu = false;
+    for (int i = 0; i < params.state_options.num_cameras; i++) {
+      double time_imu = msg_imu_current->header.stamp.toSec();
+      double time_cam = msg_images_current.at(i)->header.stamp.toSec();
+      if (time_imu <= time_cam) {
+        should_process_imu = true;
+      }
+    }
+    if (should_process_imu) {
       // convert into correct format
       ov_core::ImuData message;
-      message.timestamp = (*s2).header.stamp.toSec();
-      message.wm << (*s2).angular_velocity.x, (*s2).angular_velocity.y, (*s2).angular_velocity.z;
-      message.am << (*s2).linear_acceleration.x, (*s2).linear_acceleration.y, (*s2).linear_acceleration.z;
+      message.timestamp = msg_imu_current->header.stamp.toSec();
+      message.wm << msg_imu_current->angular_velocity.x, msg_imu_current->angular_velocity.y, msg_imu_current->angular_velocity.z;
+      message.am << msg_imu_current->linear_acceleration.x, msg_imu_current->linear_acceleration.y, msg_imu_current->linear_acceleration.z;
       // send it to our VIO system
+      // ROS_ERROR("%.15f = imu time",msg_imu_current->header.stamp.toSec()-time_init.toSec());
       sys->feed_measurement_imu(message);
       viz->visualize();
       viz->visualize_odometry(message.timestamp);
+      // move forward in time
+      msg_imu_current = msg_imu_next;
+      view_imu_iter++;
+      msg_imu_next = view_imu_iter->instantiate<sensor_msgs::Imu>();
+      continue;
     }
 
-    // Handle CAMERA measurement
-    for (const auto &pair : topic_cameras) {
-      sensor_msgs::Image::ConstPtr s0 = m.instantiate<sensor_msgs::Image>();
-      if (s0 != nullptr && m.getTopic() == pair.second) {
-        // Get the image
-        cv_bridge::CvImageConstPtr cv_ptr;
-        try {
-          cv_ptr = cv_bridge::toCvShare(s0, sensor_msgs::image_encodings::MONO8);
-        } catch (cv_bridge::Exception &e) {
-          ROS_ERROR("cv_bridge exception: %s", e.what());
-          continue;
+    // If we are stereo, then we should collect both the left and right
+    if (params.state_options.num_cameras == 2) {
+
+      // Now lets do some logic to find two images which are next to each other
+      // We want to ensure that our stereo pair are very close to occurring at the same time
+      bool have_found_pair = false;
+      while (!have_found_pair && view_cameras_iterators.at(0) != view_cameras.at(0)->end() &&
+             view_cameras_iterators.at(1) != view_cameras.at(1)->end()) {
+
+        // Get left and right cameras
+        auto msg_cam0 = msg_images_current.at(0);
+        auto msg_cam1 = msg_images_current.at(1);
+        auto msg_cam0_next = msg_images_next.at(0);
+        auto msg_cam1_next = msg_images_next.at(1);
+
+        // timestamps
+        double time0 = msg_cam0->header.stamp.toSec();
+        double time1 = msg_cam1->header.stamp.toSec();
+        double time0_next = msg_cam0_next->header.stamp.toSec();
+        double time1_next = msg_cam1_next->header.stamp.toSec();
+
+        // We will have a match if the current left and right images are closer then the next one
+        // Consider the case that we drop an image:
+        //    (L1) L2 (R2) R3 <- current pointers are at L1 and R2
+        //    In this case, we dropped the R1 image, thus we should skip the L1 image
+        //    We can check to see that L1 is further away compared to L2 from R2
+        //    Thus we should skip the L1 frame (advance the bag forward) and check this logic again!
+        if (std::abs(time1 - time0) < std::abs(time1_next - time0) && std::abs(time0 - time1) < std::abs(time0_next - time1)) {
+          have_found_pair = true;
+        } else if (std::abs(time1 - time0) >= std::abs(time1_next - time0)) {
+          // ROS_WARN("skipping cam1 (%.4f >= %.4f)",std::abs(time1-time0), std::abs(time1_next-time0));
+          msg_images_current.at(1) = msg_images_next.at(1);
+          view_cameras_iterators.at(1)++;
+          msg_images_next.at(1) = view_cameras_iterators.at(1)->instantiate<sensor_msgs::Image>();
+        } else {
+          // ROS_WARN("skipping cam0 (%.4f >= %.4f)",std::abs(time0-time1), std::abs(time0_next-time1));
+          msg_images_current.at(0) = msg_images_next.at(0);
+          view_cameras_iterators.at(0)++;
+          msg_images_next.at(0) = view_cameras_iterators.at(0)->instantiate<sensor_msgs::Image>();
         }
-        // Save to our temp variable
-        image_buffer[pair.first] = {cv_ptr->header.stamp.toSec(), cv_ptr->image.clone()};
       }
-    }
 
-    // MONO: Now loop through our buffer and see if we have have any we can send to the VIO
-    auto it0 = image_buffer.begin();
-    while (it0 != image_buffer.end()) {
-      // skip if a stereo image
-      if (std::find(stereo_cam_ids.begin(), stereo_cam_ids.end(), it0->first) != stereo_cam_ids.end()) {
-        it0++;
-        continue;
+      // Break out if we have ended
+      if (view_cameras_iterators.at(0) == view_cameras.at(0)->end() || view_cameras_iterators.at(1) == view_cameras.at(1)->end()) {
+        break;
       }
-      // process once we have initialized with the GT
+
+      // Check if we should initialize using the groundtruth (always use left)
       Eigen::Matrix<double, 17, 1> imustate;
-      if (!gt_states.empty() && !sys->initialized() && DatasetReader::get_gt_state(it0->second.first, imustate, gt_states)) {
+      if (!gt_states.empty() && !sys->initialized() &&
+          DatasetReader::get_gt_state(msg_images_current.at(0)->header.stamp.toSec(), imustate, gt_states)) {
         // biases are pretty bad normally, so zero them
         // imustate.block(11,0,6,1).setZero();
         sys->initialize_with_gt(imustate);
-      } else if (gt_states.empty() || sys->initialized()) {
-        ov_core::CameraData message;
-        message.timestamp = it0->second.first;
-        message.sensor_ids.push_back(it0->first);
-        message.images.push_back(it0->second.second);
-        sys->feed_measurement_camera(message);
       }
-      it0 = image_buffer.erase(it0);
-    }
 
-    // STEREO: Now loop through our buffer and see if we have have any we can send to the VIO
-    for (const auto &stereo : params.stereo_pairs) {
-      // skip if we don't have both images
-      if (image_buffer.find(stereo.first) == image_buffer.end() || image_buffer.find(stereo.second) == image_buffer.end())
+      // Get the image
+      cv_bridge::CvImageConstPtr cv_ptr0, cv_ptr1;
+      try {
+        cv_ptr0 = cv_bridge::toCvShare(msg_images_current.at(0), sensor_msgs::image_encodings::MONO8);
+        cv_ptr1 = cv_bridge::toCvShare(msg_images_current.at(1), sensor_msgs::image_encodings::MONO8);
+      } catch (cv_bridge::Exception &e) {
+        ROS_ERROR("cv_bridge exception: %s", e.what());
+        msg_images_current.at(0) = msg_images_next.at(0);
+        view_cameras_iterators.at(0)++;
+        msg_images_next.at(0) = view_cameras_iterators.at(0)->instantiate<sensor_msgs::Image>();
+        msg_images_current.at(1) = msg_images_next.at(1);
+        view_cameras_iterators.at(1)++;
+        msg_images_next.at(1) = view_cameras_iterators.at(1)->instantiate<sensor_msgs::Image>();
         continue;
-      // process once we have initialized with the GT
+      }
+
+      // Create viomanager message datatype
+      ov_core::CameraData message;
+      message.timestamp = msg_images_current.at(0)->header.stamp.toSec();
+      message.sensor_ids.push_back(0);
+      message.sensor_ids.push_back(1);
+      message.images.push_back(cv_ptr0->image.clone());
+      message.images.push_back(cv_ptr1->image.clone());
+      if (sys->get_params().use_mask) {
+        message.masks.push_back(sys->get_params().masks.at(0));
+        message.masks.push_back(sys->get_params().masks.at(1));
+      } else {
+        // message.masks.push_back(cv::Mat(cv_ptr0->image.rows, cv_ptr0->image.cols, CV_8UC1, cv::Scalar(255)));
+        message.masks.push_back(cv::Mat::zeros(cv_ptr0->image.rows, cv_ptr0->image.cols, CV_8UC1));
+        message.masks.push_back(cv::Mat::zeros(cv_ptr1->image.rows, cv_ptr1->image.cols, CV_8UC1));
+      }
+      // ROS_ERROR("%.15f = cam %d time",msg_images_current.at(0)->header.stamp.toSec()-time_init.toSec(), 0);
+      // ROS_ERROR("%.15f = cam %d time",msg_images_current.at(1)->header.stamp.toSec()-time_init.toSec(), 1);
+      // ROS_ERROR("(difference is %.15f)",msg_images_current.at(1)->header.stamp.toSec()-msg_images_current.at(0)->header.stamp.toSec());
+      sys->feed_measurement_camera(message);
+
+      // move forward in time
+      msg_images_current.at(0) = msg_images_next.at(0);
+      view_cameras_iterators.at(0)++;
+      msg_images_next.at(0) = view_cameras_iterators.at(0)->instantiate<sensor_msgs::Image>();
+      msg_images_current.at(1) = msg_images_next.at(1);
+      view_cameras_iterators.at(1)++;
+      msg_images_next.at(1) = view_cameras_iterators.at(1)->instantiate<sensor_msgs::Image>();
+
+    } else {
+
+      // Find the camera which should be processed (smallest time)
+      int smallest_cam = 0;
+      for (int i = 0; i < params.state_options.num_cameras; i++) {
+        double time_cam0 = msg_images_current.at(smallest_cam)->header.stamp.toSec();
+        double time_cam1 = msg_images_current.at(i)->header.stamp.toSec();
+        if (time_cam1 < time_cam0) {
+          smallest_cam = i;
+        }
+      }
+
+      // Check if we should initialize using the groundtruth
+      auto msg_camera = msg_images_current.at(smallest_cam);
       Eigen::Matrix<double, 17, 1> imustate;
-      if (!gt_states.empty() && !sys->initialized() &&
-          DatasetReader::get_gt_state(image_buffer.at(stereo.first).first, imustate, gt_states)) {
+      if (!gt_states.empty() && !sys->initialized() && DatasetReader::get_gt_state(msg_camera->header.stamp.toSec(), imustate, gt_states)) {
         // biases are pretty bad normally, so zero them
         // imustate.block(11,0,6,1).setZero();
         sys->initialize_with_gt(imustate);
-      } else if (gt_states.empty() || sys->initialized()) {
-        ov_core::CameraData message;
-        message.timestamp = image_buffer.at(stereo.first).first;
-        message.sensor_ids.push_back(stereo.first);
-        message.sensor_ids.push_back(stereo.second);
-        message.images.push_back(image_buffer.at(stereo.first).second);
-        message.images.push_back(image_buffer.at(stereo.second).second);
-        sys->feed_measurement_camera(message);
       }
-      image_buffer.erase(stereo.first);
-      image_buffer.erase(stereo.second);
+
+      // Get the image
+      cv_bridge::CvImageConstPtr cv_ptr;
+      try {
+        cv_ptr = cv_bridge::toCvShare(msg_camera, sensor_msgs::image_encodings::MONO8);
+      } catch (cv_bridge::Exception &e) {
+        ROS_ERROR("cv_bridge exception: %s", e.what());
+        msg_images_current.at(smallest_cam) = msg_images_next.at(smallest_cam);
+        view_cameras_iterators.at(smallest_cam)++;
+        msg_images_next.at(smallest_cam) = view_cameras_iterators.at(smallest_cam)->instantiate<sensor_msgs::Image>();
+        continue;
+      }
+
+      // Create viomanager message datatype
+      ov_core::CameraData message;
+      message.timestamp = msg_camera->header.stamp.toSec();
+      message.sensor_ids.push_back(smallest_cam);
+      message.images.push_back(cv_ptr->image.clone());
+      if (sys->get_params().use_mask) {
+        message.masks.push_back(sys->get_params().masks.at(smallest_cam));
+      } else {
+        message.masks.push_back(cv::Mat::zeros(cv_ptr->image.rows, cv_ptr->image.cols, CV_8UC1));
+      }
+      // ROS_ERROR("%.15f = cam %d time",msg_camera->header.stamp.toSec()-time_init.toSec(), smallest_cam);
+      sys->feed_measurement_camera(message);
+
+      // move forward
+      msg_images_current.at(smallest_cam) = msg_images_next.at(smallest_cam);
+      view_cameras_iterators.at(smallest_cam)++;
+      msg_images_next.at(smallest_cam) = view_cameras_iterators.at(smallest_cam)->instantiate<sensor_msgs::Image>();
     }
   }
 
diff --git a/ov_msckf/src/ros_subscribe_msckf.cpp b/ov_msckf/src/ros_subscribe_msckf.cpp
index 390ebcfab..b28d9e553 100644
--- a/ov_msckf/src/ros_subscribe_msckf.cpp
+++ b/ov_msckf/src/ros_subscribe_msckf.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <cv_bridge/cv_bridge.h>
 #include <message_filters/subscriber.h>
 #include <message_filters/sync_policies/approximate_time.h>
@@ -69,10 +67,9 @@ int main(int argc, char **argv) {
   // Create imu subscriber
   std::string topic_imu;
   nh.param<std::string>("topic_imu", topic_imu, "/imu0");
-  ros::Subscriber subimu = nh.subscribe(topic_imu, 9999, callback_inertial);
+  ros::Subscriber subimu = nh.subscribe(topic_imu, 9999999, callback_inertial);
 
   // Create camera subscriber data vectors
-  std::vector<int> added_cam_ids;
   std::vector<ros::Subscriber> subs_cam;
   typedef message_filters::sync_policies::ApproximateTime<sensor_msgs::Image, sensor_msgs::Image> sync_pol;
   std::vector<std::unique_ptr<message_filters::Synchronizer<sync_pol>>> sync_cam;
@@ -80,11 +77,11 @@ int main(int argc, char **argv) {
 
   // Logic for sync stereo subscriber
   // https://answers.ros.org/question/96346/subscribe-to-two-image_raws-with-one-function/?answer=96491#post-id-96491
-  for (const auto &pair : params.stereo_pairs) {
+  if (params.state_options.num_cameras == 2) {
     // Read in the topics
     std::string cam_topic0, cam_topic1;
-    nh.param<std::string>("topic_camera" + std::to_string(pair.first), cam_topic0, "/cam" + std::to_string(pair.first) + "/image_raw");
-    nh.param<std::string>("topic_camera" + std::to_string(pair.second), cam_topic1, "/cam" + std::to_string(pair.second) + "/image_raw");
+    nh.param<std::string>("topic_camera" + std::to_string(0), cam_topic0, "/cam" + std::to_string(0) + "/image_raw");
+    nh.param<std::string>("topic_camera" + std::to_string(1), cam_topic1, "/cam" + std::to_string(1) + "/image_raw");
     // Create sync filter (they have unique pointers internally, so we have to use move logic here...)
     auto image_sub0 = std::unique_ptr<message_filters::Subscriber<sensor_msgs::Image>>(
         new message_filters::Subscriber<sensor_msgs::Image>(nh, cam_topic0, 5));
@@ -92,28 +89,23 @@ int main(int argc, char **argv) {
         new message_filters::Subscriber<sensor_msgs::Image>(nh, cam_topic1, 5));
     auto sync = std::unique_ptr<message_filters::Synchronizer<sync_pol>>(
         new message_filters::Synchronizer<sync_pol>(sync_pol(5), *image_sub0, *image_sub1));
-    sync->registerCallback(boost::bind(&callback_stereo, _1, _2, pair.first, pair.second));
+    sync->registerCallback(boost::bind(&callback_stereo, _1, _2, 0, 1));
     // Append to our vector of subscribers
-    added_cam_ids.push_back(pair.first);
-    added_cam_ids.push_back(pair.second);
     sync_cam.push_back(std::move(sync));
     sync_subs_cam.push_back(std::move(image_sub0));
     sync_subs_cam.push_back(std::move(image_sub1));
     ROS_INFO("subscribing to cam (stereo): %s", cam_topic0.c_str());
     ROS_INFO("subscribing to cam (stereo): %s", cam_topic1.c_str());
-  }
-
-  // Now we should add any non-stereo callbacks here
-  for (int i = 0; i < params.state_options.num_cameras; i++) {
-    // Skip if already have been added
-    if (std::find(added_cam_ids.begin(), added_cam_ids.end(), i) != added_cam_ids.end())
-      continue;
-    // read in the topic
-    std::string cam_topic;
-    nh.param<std::string>("topic_camera" + std::to_string(i), cam_topic, "/cam" + std::to_string(i) + "/image_raw");
-    // create subscriber
-    subs_cam.push_back(nh.subscribe<sensor_msgs::Image>(cam_topic, 5, boost::bind(callback_monocular, _1, i)));
-    ROS_INFO("subscribing to cam (mono): %s", cam_topic.c_str());
+  } else {
+    // Now we should add any non-stereo callbacks here
+    for (int i = 0; i < params.state_options.num_cameras; i++) {
+      // read in the topic
+      std::string cam_topic;
+      nh.param<std::string>("topic_camera" + std::to_string(i), cam_topic, "/cam" + std::to_string(i) + "/image_raw");
+      // create subscriber
+      subs_cam.push_back(nh.subscribe<sensor_msgs::Image>(cam_topic, 5, boost::bind(callback_monocular, _1, i)));
+      ROS_INFO("subscribing to cam (mono): %s", cam_topic.c_str());
+    }
   }
 
   //===================================================================================
@@ -164,6 +156,14 @@ void callback_monocular(const sensor_msgs::ImageConstPtr &msg0, int cam_id0) {
   message.sensor_ids.push_back(cam_id0);
   message.images.push_back(cv_ptr->image.clone());
 
+  // Load the mask if we are using it, else it is empty
+  // TODO: in the future we should get this from external pixel segmentation
+  if (sys->get_params().use_mask) {
+    message.masks.push_back(sys->get_params().masks.at(cam_id0));
+  } else {
+    message.masks.push_back(cv::Mat::zeros(cv_ptr->image.rows, cv_ptr->image.cols, CV_8UC1));
+  }
+
   // send it to our VIO system
   sys->feed_measurement_camera(message);
 }
@@ -196,6 +196,17 @@ void callback_stereo(const sensor_msgs::ImageConstPtr &msg0, const sensor_msgs::
   message.images.push_back(cv_ptr0->image.clone());
   message.images.push_back(cv_ptr1->image.clone());
 
+  // Load the mask if we are using it, else it is empty
+  // TODO: in the future we should get this from external pixel segmentation
+  if (sys->get_params().use_mask) {
+    message.masks.push_back(sys->get_params().masks.at(cam_id0));
+    message.masks.push_back(sys->get_params().masks.at(cam_id1));
+  } else {
+    // message.masks.push_back(cv::Mat(cv_ptr0->image.rows, cv_ptr0->image.cols, CV_8UC1, cv::Scalar(255)));
+    message.masks.push_back(cv::Mat::zeros(cv_ptr0->image.rows, cv_ptr0->image.cols, CV_8UC1));
+    message.masks.push_back(cv::Mat::zeros(cv_ptr1->image.rows, cv_ptr1->image.cols, CV_8UC1));
+  }
+
   // send it to our VIO system
   sys->feed_measurement_camera(message);
 }
diff --git a/ov_msckf/src/run_simulation.cpp b/ov_msckf/src/run_simulation.cpp
index 3b665e9bd..ff827bda2 100644
--- a/ov_msckf/src/run_simulation.cpp
+++ b/ov_msckf/src/run_simulation.cpp
@@ -19,8 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-
 #include <csignal>
 #include <memory>
 
@@ -31,7 +29,7 @@
 #include "utils/parse_cmd.h"
 #include "utils/sensor_data.h"
 
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
 #include "core/RosVisualizer.h"
 #include "utils/parse_ros.h"
 #include <ros/ros.h>
@@ -41,7 +39,7 @@ using namespace ov_msckf;
 
 std::shared_ptr<Simulator> sim;
 std::shared_ptr<VioManager> sys;
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
 std::shared_ptr<RosVisualizer> viz;
 #endif
 
@@ -53,7 +51,7 @@ int main(int argc, char **argv) {
 
   // Read in our parameters
   VioManagerOptions params;
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   ros::init(argc, argv, "test_simulation");
   ros::NodeHandle nh("~");
   params = parse_ros_nodehandler(nh);
@@ -64,7 +62,7 @@ int main(int argc, char **argv) {
   // Create our VIO system
   sim = std::make_shared<Simulator>(params);
   sys = std::make_shared<VioManager>(params);
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   viz = std::make_shared<RosVisualizer>(nh, sys, sim);
 #endif
 
@@ -99,7 +97,7 @@ int main(int argc, char **argv) {
 
   // Step through the rosbag
   signal(SIGINT, signal_callback_handler);
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   while (sim->ok() && ros::ok()) {
 #else
   while (sim->ok()) {
@@ -110,7 +108,7 @@ int main(int argc, char **argv) {
     bool hasimu = sim->get_next_imu(message_imu.timestamp, message_imu.wm, message_imu.am);
     if (hasimu) {
       sys->feed_measurement_imu(message_imu);
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
       viz->visualize_odometry(message_imu.timestamp);
 #endif
     }
@@ -123,7 +121,7 @@ int main(int argc, char **argv) {
     if (hascam) {
       if (buffer_timecam != -1) {
         sys->feed_measurement_simulation(buffer_timecam, buffer_camids, buffer_feats);
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
         viz->visualize();
 #endif
       }
@@ -138,7 +136,7 @@ int main(int argc, char **argv) {
   //===================================================================================
 
   // Final visualization
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   viz->visualize_final();
 #endif
 
diff --git a/ov_msckf/src/sim/Simulator.cpp b/ov_msckf/src/sim/Simulator.cpp
index 83041082b..ff7596cf8 100644
--- a/ov_msckf/src/sim/Simulator.cpp
+++ b/ov_msckf/src/sim/Simulator.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "Simulator.h"
 
 using namespace ov_msckf;
diff --git a/ov_msckf/src/sim/Simulator.h b/ov_msckf/src/sim/Simulator.h
index f298309ee..070c18b50 100644
--- a/ov_msckf/src/sim/Simulator.h
+++ b/ov_msckf/src/sim/Simulator.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_SIMULATOR_H
 #define OV_MSCKF_SIMULATOR_H
 
diff --git a/ov_msckf/src/state/Propagator.cpp b/ov_msckf/src/state/Propagator.cpp
index d42f592f4..b06170475 100644
--- a/ov_msckf/src/state/Propagator.cpp
+++ b/ov_msckf/src/state/Propagator.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "Propagator.h"
 
 using namespace ov_core;
diff --git a/ov_msckf/src/state/Propagator.h b/ov_msckf/src/state/Propagator.h
index 956b79c48..77a85ca5b 100644
--- a/ov_msckf/src/state/Propagator.h
+++ b/ov_msckf/src/state/Propagator.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_STATE_PROPAGATOR_H
 #define OV_MSCKF_STATE_PROPAGATOR_H
 
diff --git a/ov_msckf/src/state/State.cpp b/ov_msckf/src/state/State.cpp
index a41c16ada..abb45afcf 100644
--- a/ov_msckf/src/state/State.cpp
+++ b/ov_msckf/src/state/State.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "State.h"
 
 #include <memory>
@@ -59,7 +58,6 @@ State::State(StateOptions &options) {
     // Add these to the corresponding maps
     _calib_IMUtoCAM.insert({i, pose});
     _cam_intrinsics.insert({i, intrin});
-    _cam_intrinsics_model.insert({i, false});
 
     // If calibrating camera-imu pose, add to variables
     if (_options.do_calib_camera_pose) {
diff --git a/ov_msckf/src/state/State.h b/ov_msckf/src/state/State.h
index 2561fbab4..bc43812e9 100644
--- a/ov_msckf/src/state/State.h
+++ b/ov_msckf/src/state/State.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_STATE_H
 #define OV_MSCKF_STATE_H
 
@@ -28,6 +27,7 @@
 #include <vector>
 
 #include "StateOptions.h"
+#include "cam/CamBase.h"
 #include "types/IMU.h"
 #include "types/Landmark.h"
 #include "types/PoseJPL.h"
@@ -104,8 +104,8 @@ class State {
   /// Camera intrinsics
   std::unordered_map<size_t, std::shared_ptr<Vec>> _cam_intrinsics;
 
-  /// What distortion model we are using (false=radtan, true=fisheye)
-  std::unordered_map<size_t, bool> _cam_intrinsics_model;
+  /// Camera intrinsics camera objects
+  std::unordered_map<size_t, std::shared_ptr<CamBase>> _cam_intrinsics_cameras;
 
 private:
   // Define that the state helper is a friend class of this class
diff --git a/ov_msckf/src/state/StateHelper.cpp b/ov_msckf/src/state/StateHelper.cpp
index 5bdd3cb5e..15570a4bc 100644
--- a/ov_msckf/src/state/StateHelper.cpp
+++ b/ov_msckf/src/state/StateHelper.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "StateHelper.h"
 
 using namespace ov_core;
@@ -174,6 +173,14 @@ void StateHelper::EKFUpdate(std::shared_ptr<State> state, const std::vector<std:
   for (size_t i = 0; i < state->_variables.size(); i++) {
     state->_variables.at(i)->update(dx.block(state->_variables.at(i)->id(), 0, state->_variables.at(i)->size(), 1));
   }
+
+  // If we are doing online intrinsic calibration we should update our camera objects
+  // NOTE: is this the best place to put this update logic??? probably..
+  if (state->_options.do_calib_camera_intrinsics) {
+    for (auto const &calib : state->_cam_intrinsics) {
+      state->_cam_intrinsics_cameras.at(calib.first)->set_value(calib.second->value());
+    }
+  }
 }
 
 void StateHelper::fix_4dof_gauge_freedoms(std::shared_ptr<State> state, const Eigen::Vector4d &q_GtoI) {
diff --git a/ov_msckf/src/state/StateHelper.h b/ov_msckf/src/state/StateHelper.h
index e78ba6628..69d250aae 100644
--- a/ov_msckf/src/state/StateHelper.h
+++ b/ov_msckf/src/state/StateHelper.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_STATE_HELPER_H
 #define OV_MSCKF_STATE_HELPER_H
 
diff --git a/ov_msckf/src/state/StateOptions.h b/ov_msckf/src/state/StateOptions.h
index c90dd4428..248691c39 100644
--- a/ov_msckf/src/state/StateOptions.h
+++ b/ov_msckf/src/state/StateOptions.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_STATE_OPTIONS_H
 #define OV_MSCKF_STATE_OPTIONS_H
 
@@ -71,9 +70,6 @@ struct StateOptions {
   /// Number of distinct cameras that we will observe features in
   int num_cameras = 1;
 
-  /// Number of cameras (a stereo pair is not consider unique since both images occur at the same pose timestamp)
-  int num_unique_cameras = 1;
-
   /// What representation our features are in (msckf features)
   LandmarkRepresentation::Representation feat_rep_msckf = LandmarkRepresentation::Representation::GLOBAL_3D;
 
@@ -97,7 +93,6 @@ struct StateOptions {
     printf("\t- max_msckf_in_update: %d\n", max_msckf_in_update);
     printf("\t- max_aruco: %d\n", max_aruco_features);
     printf("\t- max_cameras: %d\n", num_cameras);
-    printf("\t- num_unique_cameras: %d\n", num_unique_cameras);
     printf("\t- feat_rep_msckf: %s\n", LandmarkRepresentation::as_string(feat_rep_msckf).c_str());
     printf("\t- feat_rep_slam: %s\n", LandmarkRepresentation::as_string(feat_rep_slam).c_str());
     printf("\t- feat_rep_aruco: %s\n", LandmarkRepresentation::as_string(feat_rep_aruco).c_str());
diff --git a/ov_msckf/src/test_sim_meas.cpp b/ov_msckf/src/test_sim_meas.cpp
index c732ba8bb..f5c1fbea3 100644
--- a/ov_msckf/src/test_sim_meas.cpp
+++ b/ov_msckf/src/test_sim_meas.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include <cmath>
 #include <csignal>
 #include <deque>
@@ -31,7 +30,7 @@
 #include <boost/date_time/posix_time/posix_time.hpp>
 #include <boost/filesystem.hpp>
 
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
 #include "utils/parse_ros.h"
 #include <ros/ros.h>
 #endif
@@ -48,9 +47,9 @@ void signal_callback_handler(int signum) { std::exit(signum); }
 // Main function
 int main(int argc, char **argv) {
 
-  // Read in our paramters
+  // Read in our parameters
   VioManagerOptions params;
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   ros::init(argc, argv, "test_sim_meas");
   ros::NodeHandle nh("~");
   params = parse_ros_nodehandler(nh);
diff --git a/ov_msckf/src/test_sim_repeat.cpp b/ov_msckf/src/test_sim_repeat.cpp
index 29bd9fbf9..d2b35bd48 100644
--- a/ov_msckf/src/test_sim_repeat.cpp
+++ b/ov_msckf/src/test_sim_repeat.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include <cmath>
 #include <csignal>
 #include <deque>
@@ -30,7 +29,7 @@
 #include <boost/date_time/posix_time/posix_time.hpp>
 #include <boost/filesystem.hpp>
 
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
 #include <ros/ros.h>
 #endif
 
@@ -55,7 +54,7 @@ int main(int argc, char **argv) {
 
   // Create the simulator
   VioManagerOptions params1;
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   ros::init(argc, argv, "test_sim_repeat");
   ros::NodeHandle nh1("~");
   params1 = parse_ros_nodehandler(nh1);
@@ -100,7 +99,7 @@ int main(int argc, char **argv) {
 
   // Create the simulator
   VioManagerOptions params2;
-#ifdef ROS_AVAILABLE
+#if ROS_AVAILABLE
   ros::NodeHandle nh2("~");
   params2 = parse_ros_nodehandler(nh2);
 #else
diff --git a/ov_msckf/src/update/UpdaterHelper.cpp b/ov_msckf/src/update/UpdaterHelper.cpp
index ad1739c59..b4d903e8e 100644
--- a/ov_msckf/src/update/UpdaterHelper.cpp
+++ b/ov_msckf/src/update/UpdaterHelper.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "UpdaterHelper.h"
 
 using namespace ov_core;
@@ -185,121 +184,6 @@ void UpdaterHelper::get_feature_jacobian_representation(std::shared_ptr<State> s
   assert(false);
 }
 
-void UpdaterHelper::get_feature_jacobian_intrinsics(std::shared_ptr<State> state, const Eigen::Vector2d &uv_norm, bool isfisheye,
-                                                    Eigen::Matrix<double, 8, 1> cam_d, Eigen::Matrix<double, 2, 2> &dz_dzn,
-                                                    Eigen::Matrix<double, 2, 8> &dz_dzeta) {
-
-  // Calculate distortion uv and jacobian
-  if (isfisheye) {
-
-    // Calculate distorted coordinates for fisheye
-    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-    double theta = std::atan(r);
-    double theta_d = theta + cam_d(4) * std::pow(theta, 3) + cam_d(5) * std::pow(theta, 5) + cam_d(6) * std::pow(theta, 7) +
-                     cam_d(7) * std::pow(theta, 9);
-
-    // Handle when r is small (meaning our xy is near the camera center)
-    double inv_r = (r > 1e-8) ? 1.0 / r : 1.0;
-    double cdist = (r > 1e-8) ? theta_d * inv_r : 1.0;
-
-    // Jacobian of distorted pixel to "normalized" pixel
-    Eigen::Matrix<double, 2, 2> duv_dxy = Eigen::Matrix<double, 2, 2>::Zero();
-    duv_dxy << cam_d(0), 0, 0, cam_d(1);
-
-    // Jacobian of "normalized" pixel to normalized pixel
-    Eigen::Matrix<double, 2, 2> dxy_dxyn = Eigen::Matrix<double, 2, 2>::Zero();
-    dxy_dxyn << theta_d * inv_r, 0, 0, theta_d * inv_r;
-
-    // Jacobian of "normalized" pixel to r
-    Eigen::Matrix<double, 2, 1> dxy_dr = Eigen::Matrix<double, 2, 1>::Zero();
-    dxy_dr << -uv_norm(0) * theta_d * inv_r * inv_r, -uv_norm(1) * theta_d * inv_r * inv_r;
-
-    // Jacobian of r pixel to normalized xy
-    Eigen::Matrix<double, 1, 2> dr_dxyn = Eigen::Matrix<double, 1, 2>::Zero();
-    dr_dxyn << uv_norm(0) * inv_r, uv_norm(1) * inv_r;
-
-    // Jacobian of "normalized" pixel to theta_d
-    Eigen::Matrix<double, 2, 1> dxy_dthd = Eigen::Matrix<double, 2, 1>::Zero();
-    dxy_dthd << uv_norm(0) * inv_r, uv_norm(1) * inv_r;
-
-    // Jacobian of theta_d to theta
-    double dthd_dth = 1 + 3 * cam_d(4) * std::pow(theta, 2) + 5 * cam_d(5) * std::pow(theta, 4) + 7 * cam_d(6) * std::pow(theta, 6) +
-                      9 * cam_d(7) * std::pow(theta, 8);
-
-    // Jacobian of theta to r
-    double dth_dr = 1 / (r * r + 1);
-
-    // Total Jacobian wrt normalized pixel coordinates
-    dz_dzn = duv_dxy * (dxy_dxyn + (dxy_dr + dxy_dthd * dthd_dth * dth_dr) * dr_dxyn);
-
-    // Compute the Jacobian in respect to the intrinsics if we are calibrating
-    if (state->_options.do_calib_camera_intrinsics) {
-
-      // Calculate distorted coordinates for fisheye
-      double x1 = uv_norm(0) * cdist;
-      double y1 = uv_norm(1) * cdist;
-
-      // Jacobian
-      dz_dzeta(0, 0) = x1;
-      dz_dzeta(0, 2) = 1;
-      dz_dzeta(0, 4) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 3);
-      dz_dzeta(0, 5) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 5);
-      dz_dzeta(0, 6) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 7);
-      dz_dzeta(0, 7) = cam_d(0) * uv_norm(0) * inv_r * std::pow(theta, 9);
-      dz_dzeta(1, 1) = y1;
-      dz_dzeta(1, 3) = 1;
-      dz_dzeta(1, 4) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 3);
-      dz_dzeta(1, 5) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 5);
-      dz_dzeta(1, 6) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 7);
-      dz_dzeta(1, 7) = cam_d(1) * uv_norm(1) * inv_r * std::pow(theta, 9);
-    }
-
-  } else {
-
-    // Calculate distorted coordinates for radial
-    double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-    double r_2 = r * r;
-    double r_4 = r_2 * r_2;
-
-    // Jacobian of distorted pixel to normalized pixel
-    double x = uv_norm(0);
-    double y = uv_norm(1);
-    double x_2 = uv_norm(0) * uv_norm(0);
-    double y_2 = uv_norm(1) * uv_norm(1);
-    double x_y = uv_norm(0) * uv_norm(1);
-    dz_dzn(0, 0) = cam_d(0) * ((1 + cam_d(4) * r_2 + cam_d(5) * r_4) + (2 * cam_d(4) * x_2 + 4 * cam_d(5) * x_2 * r) + 2 * cam_d(6) * y +
-                               (2 * cam_d(7) * x + 4 * cam_d(7) * x));
-    dz_dzn(0, 1) = cam_d(0) * (2 * cam_d(4) * x_y + 4 * cam_d(5) * x_y * r + 2 * cam_d(6) * x + 2 * cam_d(7) * y);
-    dz_dzn(1, 0) = cam_d(1) * (2 * cam_d(4) * x_y + 4 * cam_d(5) * x_y * r + 2 * cam_d(6) * x + 2 * cam_d(7) * y);
-    dz_dzn(1, 1) = cam_d(1) * ((1 + cam_d(4) * r_2 + cam_d(5) * r_4) + (2 * cam_d(4) * y_2 + 4 * cam_d(5) * y_2 * r) + 2 * cam_d(7) * x +
-                               (2 * cam_d(6) * y + 4 * cam_d(6) * y));
-
-    // Compute the Jacobian in respect to the intrinsics if we are calibrating
-    if (state->_options.do_calib_camera_intrinsics) {
-
-      // Calculate distorted coordinates for radtan
-      double x1 = uv_norm(0) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + 2 * cam_d(6) * uv_norm(0) * uv_norm(1) +
-                  cam_d(7) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
-      double y1 = uv_norm(1) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + cam_d(6) * (r_2 + 2 * uv_norm(1) * uv_norm(1)) +
-                  2 * cam_d(7) * uv_norm(0) * uv_norm(1);
-
-      // Jacobian
-      dz_dzeta(0, 0) = x1;
-      dz_dzeta(0, 2) = 1;
-      dz_dzeta(0, 4) = cam_d(0) * uv_norm(0) * r_2;
-      dz_dzeta(0, 5) = cam_d(0) * uv_norm(0) * r_4;
-      dz_dzeta(0, 6) = 2 * cam_d(0) * uv_norm(0) * uv_norm(1);
-      dz_dzeta(0, 7) = cam_d(0) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
-      dz_dzeta(1, 1) = y1;
-      dz_dzeta(1, 3) = 1;
-      dz_dzeta(1, 4) = cam_d(1) * uv_norm(1) * r_2;
-      dz_dzeta(1, 5) = cam_d(1) * uv_norm(1) * r_4;
-      dz_dzeta(1, 6) = cam_d(1) * (r_2 + 2 * uv_norm(1) * uv_norm(1));
-      dz_dzeta(1, 7) = 2 * cam_d(1) * uv_norm(0) * uv_norm(1);
-    }
-  }
-}
-
 void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, UpdaterHelperFeature &feature, Eigen::MatrixXd &H_f,
                                               Eigen::MatrixXd &H_x, Eigen::VectorXd &res, std::vector<std::shared_ptr<Type>> &x_order) {
 
@@ -381,11 +265,11 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
     // Assert that we have an anchor pose for this feature
     assert(feature.anchor_cam_id != -1);
     // Get calibration for our anchor camera
-    Eigen::Matrix<double, 3, 3> R_ItoC = state->_calib_IMUtoCAM.at(feature.anchor_cam_id)->Rot();
-    Eigen::Matrix<double, 3, 1> p_IinC = state->_calib_IMUtoCAM.at(feature.anchor_cam_id)->pos();
+    Eigen::Matrix3d R_ItoC = state->_calib_IMUtoCAM.at(feature.anchor_cam_id)->Rot();
+    Eigen::Vector3d p_IinC = state->_calib_IMUtoCAM.at(feature.anchor_cam_id)->pos();
     // Anchor pose orientation and position
-    Eigen::Matrix<double, 3, 3> R_GtoI = state->_clones_IMU.at(feature.anchor_clone_timestamp)->Rot();
-    Eigen::Matrix<double, 3, 1> p_IinG = state->_clones_IMU.at(feature.anchor_clone_timestamp)->pos();
+    Eigen::Matrix3d R_GtoI = state->_clones_IMU.at(feature.anchor_clone_timestamp)->Rot();
+    Eigen::Vector3d p_IinG = state->_clones_IMU.at(feature.anchor_clone_timestamp)->pos();
     // Feature in the global frame
     p_FinG = R_GtoI.transpose() * R_ItoC.transpose() * (feature.p_FinA - p_IinC) + p_IinG;
   }
@@ -425,9 +309,8 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
     // Our calibration between the IMU and CAMi frames
     std::shared_ptr<Vec> distortion = state->_cam_intrinsics.at(pair.first);
     std::shared_ptr<PoseJPL> calibration = state->_calib_IMUtoCAM.at(pair.first);
-    Eigen::Matrix<double, 3, 3> R_ItoC = calibration->Rot();
-    Eigen::Matrix<double, 3, 1> p_IinC = calibration->pos();
-    Eigen::Matrix<double, 8, 1> cam_d = distortion->value();
+    Eigen::Matrix3d R_ItoC = calibration->Rot();
+    Eigen::Vector3d p_IinC = calibration->pos();
 
     // Loop through all measurements for this specific camera
     for (size_t m = 0; m < feature.timestamps[pair.first].size(); m++) {
@@ -437,55 +320,23 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
 
       // Get current IMU clone state
       std::shared_ptr<PoseJPL> clone_Ii = state->_clones_IMU.at(feature.timestamps[pair.first].at(m));
-      Eigen::Matrix<double, 3, 3> R_GtoIi = clone_Ii->Rot();
-      Eigen::Matrix<double, 3, 1> p_IiinG = clone_Ii->pos();
+      Eigen::Matrix3d R_GtoIi = clone_Ii->Rot();
+      Eigen::Vector3d p_IiinG = clone_Ii->pos();
 
       // Get current feature in the IMU
-      Eigen::Matrix<double, 3, 1> p_FinIi = R_GtoIi * (p_FinG - p_IiinG);
+      Eigen::Vector3d p_FinIi = R_GtoIi * (p_FinG - p_IiinG);
 
       // Project the current feature into the current frame of reference
-      Eigen::Matrix<double, 3, 1> p_FinCi = R_ItoC * p_FinIi + p_IinC;
-      Eigen::Matrix<double, 2, 1> uv_norm;
+      Eigen::Vector3d p_FinCi = R_ItoC * p_FinIi + p_IinC;
+      Eigen::Vector2d uv_norm;
       uv_norm << p_FinCi(0) / p_FinCi(2), p_FinCi(1) / p_FinCi(2);
 
-      // Distort the normalized coordinates (false=radtan, true=fisheye)
-      Eigen::Matrix<double, 2, 1> uv_dist;
-
-      // Calculate distortion uv and jacobian
-      if (state->_cam_intrinsics_model.at(pair.first)) {
-
-        // Calculate distorted coordinates for fisheye
-        double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-        double theta = std::atan(r);
-        double theta_d = theta + cam_d(4) * std::pow(theta, 3) + cam_d(5) * std::pow(theta, 5) + cam_d(6) * std::pow(theta, 7) +
-                         cam_d(7) * std::pow(theta, 9);
-
-        // Handle when r is small (meaning our xy is near the camera center)
-        double inv_r = (r > 1e-8) ? 1.0 / r : 1.0;
-        double cdist = (r > 1e-8) ? theta_d * inv_r : 1.0;
-
-        // Calculate distorted coordinates for fisheye
-        double x1 = uv_norm(0) * cdist;
-        double y1 = uv_norm(1) * cdist;
-        uv_dist(0) = cam_d(0) * x1 + cam_d(2);
-        uv_dist(1) = cam_d(1) * y1 + cam_d(3);
-
-      } else {
-
-        // Calculate distorted coordinates for radial
-        double r = std::sqrt(uv_norm(0) * uv_norm(0) + uv_norm(1) * uv_norm(1));
-        double r_2 = r * r;
-        double r_4 = r_2 * r_2;
-        double x1 = uv_norm(0) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + 2 * cam_d(6) * uv_norm(0) * uv_norm(1) +
-                    cam_d(7) * (r_2 + 2 * uv_norm(0) * uv_norm(0));
-        double y1 = uv_norm(1) * (1 + cam_d(4) * r_2 + cam_d(5) * r_4) + cam_d(6) * (r_2 + 2 * uv_norm(1) * uv_norm(1)) +
-                    2 * cam_d(7) * uv_norm(0) * uv_norm(1);
-        uv_dist(0) = cam_d(0) * x1 + cam_d(2);
-        uv_dist(1) = cam_d(1) * y1 + cam_d(3);
-      }
+      // Distort the normalized coordinates (radtan or fisheye)
+      Eigen::Vector2d uv_dist;
+      uv_dist = state->_cam_intrinsics_cameras.at(pair.first)->distort_d(uv_norm);
 
       // Our residual
-      Eigen::Matrix<double, 2, 1> uv_m;
+      Eigen::Vector2d uv_m;
       uv_m << (double)feature.uvs[pair.first].at(m)(0), (double)feature.uvs[pair.first].at(m)(1);
       res.block(2 * c, 0, 2, 1) = uv_m - uv_dist;
 
@@ -505,19 +356,18 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
       }
 
       // Compute Jacobians in respect to normalized image coordinates and possibly the camera intrinsics
-      Eigen::Matrix<double, 2, 2> dz_dzn = Eigen::Matrix<double, 2, 2>::Zero();
-      Eigen::Matrix<double, 2, 8> dz_dzeta = Eigen::Matrix<double, 2, 8>::Zero();
-      UpdaterHelper::get_feature_jacobian_intrinsics(state, uv_norm, state->_cam_intrinsics_model.at(pair.first), cam_d, dz_dzn, dz_dzeta);
+      Eigen::MatrixXd dz_dzn, dz_dzeta;
+      state->_cam_intrinsics_cameras.at(pair.first)->compute_distort_jacobian(uv_norm, dz_dzn, dz_dzeta);
 
       // Normalized coordinates in respect to projection function
-      Eigen::Matrix<double, 2, 3> dzn_dpfc = Eigen::Matrix<double, 2, 3>::Zero();
+      Eigen::MatrixXd dzn_dpfc = Eigen::MatrixXd::Zero(2, 3);
       dzn_dpfc << 1 / p_FinCi(2), 0, -p_FinCi(0) / (p_FinCi(2) * p_FinCi(2)), 0, 1 / p_FinCi(2), -p_FinCi(1) / (p_FinCi(2) * p_FinCi(2));
 
       // Derivative of p_FinCi in respect to p_FinIi
-      Eigen::Matrix<double, 3, 3> dpfc_dpfg = R_ItoC * R_GtoIi;
+      Eigen::MatrixXd dpfc_dpfg = R_ItoC * R_GtoIi;
 
       // Derivative of p_FinCi in respect to camera clone state
-      Eigen::Matrix<double, 3, 6> dpfc_dclone = Eigen::Matrix<double, 3, 6>::Zero();
+      Eigen::MatrixXd dpfc_dclone = Eigen::MatrixXd::Zero(3, 6);
       dpfc_dclone.block(0, 0, 3, 3).noalias() = R_ItoC * skew_x(p_FinIi);
       dpfc_dclone.block(0, 3, 3, 3) = -dpfc_dpfg;
 
@@ -525,8 +375,8 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
       //=========================================================================
 
       // Precompute some matrices
-      Eigen::Matrix<double, 2, 3> dz_dpfc = dz_dzn * dzn_dpfc;
-      Eigen::Matrix<double, 2, 3> dz_dpfg = dz_dpfc * dpfc_dpfg;
+      Eigen::MatrixXd dz_dpfc = dz_dzn * dzn_dpfc;
+      Eigen::MatrixXd dz_dpfg = dz_dpfc * dpfc_dpfg;
 
       // CHAINRULE: get the total feature Jacobian
       H_f.block(2 * c, 0, 2, H_f.cols()).noalias() = dz_dpfg * dpfg_dlambda;
@@ -547,7 +397,7 @@ void UpdaterHelper::get_feature_jacobian_full(std::shared_ptr<State> state, Upda
       if (state->_options.do_calib_camera_pose) {
 
         // Calculate the Jacobian
-        Eigen::Matrix<double, 3, 6> dpfc_dcalib = Eigen::Matrix<double, 3, 6>::Zero();
+        Eigen::MatrixXd dpfc_dcalib = Eigen::MatrixXd::Zero(3, 6);
         dpfc_dcalib.block(0, 0, 3, 3) = skew_x(p_FinCi - p_IinC);
         dpfc_dcalib.block(0, 3, 3, 3) = Eigen::Matrix<double, 3, 3>::Identity();
 
diff --git a/ov_msckf/src/update/UpdaterHelper.h b/ov_msckf/src/update/UpdaterHelper.h
index 03c176635..f01890a60 100644
--- a/ov_msckf/src/update/UpdaterHelper.h
+++ b/ov_msckf/src/update/UpdaterHelper.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_UPDATER_HELPER_H
 #define OV_MSCKF_UPDATER_HELPER_H
 
@@ -98,20 +97,6 @@ class UpdaterHelper {
   static void get_feature_jacobian_representation(std::shared_ptr<State> state, UpdaterHelperFeature &feature, Eigen::MatrixXd &H_f,
                                                   std::vector<Eigen::MatrixXd> &H_x, std::vector<std::shared_ptr<Type>> &x_order);
 
-  /**
-   * @brief This will compute the Jacobian in respect to the intrinsic calibration parameters and normalized coordinates
-   *
-   * @param state State of the filter system
-   * @param uv_norm Normalized image coordinates
-   * @param isfisheye If this feature is for a fisheye model
-   * @param cam_d Camera intrinsics values
-   * @param dz_dzn Derivative in respect to normalized coordinates
-   * @param dz_dzeta Derivative in respect to distortion paramters
-   */
-  static void get_feature_jacobian_intrinsics(std::shared_ptr<State> state, const Eigen::Vector2d &uv_norm, bool isfisheye,
-                                              Eigen::Matrix<double, 8, 1> cam_d, Eigen::Matrix<double, 2, 2> &dz_dzn,
-                                              Eigen::Matrix<double, 2, 8> &dz_dzeta);
-
   /**
    * @brief Will construct the "stacked" Jacobians for a single feature from all its measurements
    *
diff --git a/ov_msckf/src/update/UpdaterMSCKF.cpp b/ov_msckf/src/update/UpdaterMSCKF.cpp
index 352725f77..4449e1051 100644
--- a/ov_msckf/src/update/UpdaterMSCKF.cpp
+++ b/ov_msckf/src/update/UpdaterMSCKF.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "UpdaterMSCKF.h"
 
 using namespace ov_core;
diff --git a/ov_msckf/src/update/UpdaterMSCKF.h b/ov_msckf/src/update/UpdaterMSCKF.h
index 9ab2384a5..38a62928c 100644
--- a/ov_msckf/src/update/UpdaterMSCKF.h
+++ b/ov_msckf/src/update/UpdaterMSCKF.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_UPDATER_MSCKF_H
 #define OV_MSCKF_UPDATER_MSCKF_H
 
diff --git a/ov_msckf/src/update/UpdaterOptions.h b/ov_msckf/src/update/UpdaterOptions.h
index f8ef88cd7..792a08785 100644
--- a/ov_msckf/src/update/UpdaterOptions.h
+++ b/ov_msckf/src/update/UpdaterOptions.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_UPDATER_OPTIONS_H
 #define OV_MSCKF_UPDATER_OPTIONS_H
 
diff --git a/ov_msckf/src/update/UpdaterSLAM.cpp b/ov_msckf/src/update/UpdaterSLAM.cpp
index b554f4024..17a0bb880 100644
--- a/ov_msckf/src/update/UpdaterSLAM.cpp
+++ b/ov_msckf/src/update/UpdaterSLAM.cpp
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #include "UpdaterSLAM.h"
 
 #include <memory>
@@ -349,7 +348,6 @@ void UpdaterSLAM::update(std::shared_ptr<State> state, std::vector<std::shared_p
       // Else we have the full feature in our state, so just append it
       H_xf.conservativeResize(H_x.rows(), H_x.cols() + H_f.cols());
       H_xf.block(0, H_x.cols(), H_x.rows(), H_f.cols()) = H_f;
-
     }
 
     // Append to our Jacobian order vector
diff --git a/ov_msckf/src/update/UpdaterSLAM.h b/ov_msckf/src/update/UpdaterSLAM.h
index 234b37c72..35dfb50ec 100644
--- a/ov_msckf/src/update/UpdaterSLAM.h
+++ b/ov_msckf/src/update/UpdaterSLAM.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_UPDATER_SLAM_H
 #define OV_MSCKF_UPDATER_SLAM_H
 
diff --git a/ov_msckf/src/update/UpdaterZeroVelocity.cpp b/ov_msckf/src/update/UpdaterZeroVelocity.cpp
index 50f236ec8..704ba7989 100644
--- a/ov_msckf/src/update/UpdaterZeroVelocity.cpp
+++ b/ov_msckf/src/update/UpdaterZeroVelocity.cpp
@@ -297,5 +297,4 @@ bool UpdaterZeroVelocity::try_update(std::shared_ptr<State> state, double timest
   // Finally return
   last_zupt_state_timestamp = timestamp;
   return true;
-
 }
\ No newline at end of file
diff --git a/ov_msckf/src/update/UpdaterZeroVelocity.h b/ov_msckf/src/update/UpdaterZeroVelocity.h
index 43b936270..af1756129 100644
--- a/ov_msckf/src/update/UpdaterZeroVelocity.h
+++ b/ov_msckf/src/update/UpdaterZeroVelocity.h
@@ -22,10 +22,10 @@
 #ifndef OV_MSCKF_UPDATER_ZEROVELOCITY_H
 #define OV_MSCKF_UPDATER_ZEROVELOCITY_H
 
+#include "feat/FeatureDatabase.h"
 #include "state/Propagator.h"
 #include "state/State.h"
 #include "state/StateHelper.h"
-#include "feat/FeatureDatabase.h"
 #include "utils/colors.h"
 #include "utils/quat_ops.h"
 #include "utils/sensor_data.h"
@@ -55,14 +55,15 @@ class UpdaterZeroVelocity {
    * @param options Updater options (chi2 multiplier)
    * @param noises imu noise characteristics (continuous time)
    * @param db Feature tracker database with all features in it
+   * @param prop Propagator class object which can predict the state forward in time
    * @param gravity_mag Global gravity magnitude of the system (normally 9.81)
    * @param zupt_max_velocity Max velocity we should consider to do a update with
    * @param zupt_noise_multiplier Multiplier of our IMU noise matrix (default should be 1.0)
    * @param zupt_max_disparity Max disparity we should consider to do a update with
    */
-  UpdaterZeroVelocity(UpdaterOptions &options, Propagator::NoiseManager &noises, std::shared_ptr<FeatureDatabase> db, std::shared_ptr<Propagator> prop,
-                      double gravity_mag, double zupt_max_velocity,
-                      double zupt_noise_multiplier, double zupt_max_disparity)
+  UpdaterZeroVelocity(UpdaterOptions &options, Propagator::NoiseManager &noises, std::shared_ptr<FeatureDatabase> db,
+                      std::shared_ptr<Propagator> prop, double gravity_mag, double zupt_max_velocity, double zupt_noise_multiplier,
+                      double zupt_max_disparity)
       : _options(options), _noises(noises), _db(db), _prop(prop), _zupt_max_velocity(zupt_max_velocity),
         _zupt_noise_multiplier(zupt_noise_multiplier), _zupt_max_disparity(zupt_max_disparity) {
 
@@ -155,7 +156,6 @@ class UpdaterZeroVelocity {
 
   // Last timestamp we did zero velocity update with
   double last_zupt_state_timestamp = 0.0;
-
 };
 
 } // namespace ov_msckf
diff --git a/ov_msckf/src/utils/parse_cmd.h b/ov_msckf/src/utils/parse_cmd.h
index 78224eba9..8699fb84e 100644
--- a/ov_msckf/src/utils/parse_cmd.h
+++ b/ov_msckf/src/utils/parse_cmd.h
@@ -19,7 +19,6 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
 #ifndef OV_MSCKF_PARSE_CMDLINE_H
 #define OV_MSCKF_PARSE_CMDLINE_H
 
@@ -62,10 +61,6 @@ VioManagerOptions parse_command_line_arguments(int argc, char **argv) {
   app1.add_option("--max_cameras", params.state_options.num_cameras, "");
   app1.add_option("--dt_slam_delay", params.dt_slam_delay, "");
 
-  // Stereo pairs
-  std::vector<int> stereo_pairs;
-  app1.add_option("--stereo_pairs", stereo_pairs, "");
-
   // Read in what representation our feature is
   std::string feat_rep_msckf_str = "GLOBAL_3D";
   std::string feat_rep_slam_str = "GLOBAL_3D";
@@ -132,6 +127,10 @@ VioManagerOptions parse_command_line_arguments(int argc, char **argv) {
   app1.add_option("--min_px_dist", params.min_px_dist, "");
   app1.add_option("--knn_ratio", params.knn_ratio, "");
 
+  // Preprocessing histogram method
+  std::string histogram_method_str = "HISTOGRAM";
+  app1.add_option("--histogram_method", histogram_method_str, "");
+
   // Feature initializer parameters
   app1.add_option("--fi_triangulate_1d", params.featinit_options.triangulate_1d, "");
   app1.add_option("--fi_refine_features", params.featinit_options.refine_features, "");
@@ -171,43 +170,6 @@ VioManagerOptions parse_command_line_arguments(int argc, char **argv) {
     std::exit(app1.exit(e));
   }
 
-  // Read in stereo pair information
-  if (stereo_pairs.size() % 2 != 0) {
-    printf(RED "VioManager(): Specified number of stereo pair IDs needs to be even\n" RESET);
-    printf(RED "VioManager(): Example: (0,1,2,3) -> stereo tracking between 01 and 23\n" RESET);
-    std::exit(EXIT_FAILURE);
-  }
-  for (size_t i = 0; i < stereo_pairs.size(); i++) {
-    if (std::count(stereo_pairs.begin(), stereo_pairs.end(), stereo_pairs.at(i)) != 1) {
-      printf(RED "VioManager(): You can do stereo tracking between unique ids\n" RESET);
-      printf(RED "VioManager(): %d showed up multiple times\n" RESET, stereo_pairs.at(i));
-      std::exit(EXIT_FAILURE);
-    }
-    // if(stereo_pairs.at(i) >= params.state_options.num_cameras) {
-    //    printf(RED "VioManager(): Stereo pair has an id larger then the max camera\n" RESET);
-    //    printf(RED "VioManager(): %d is >= than %d\n" RESET,stereo_pairs.at(i),params.state_options.num_cameras);
-    //    std::exit(EXIT_FAILURE);
-    //}
-  }
-  std::vector<int> valid_stereo_pairs;
-  for (size_t i = 0; i < stereo_pairs.size(); i += 2) {
-    if (stereo_pairs.at(i) >= params.state_options.num_cameras || stereo_pairs.at(i + 1) >= params.state_options.num_cameras) {
-      printf(RED "ignoring invalid stereo pair: %d, %d\n" RESET, stereo_pairs.at(i), stereo_pairs.at(i + 1));
-      continue;
-    }
-    params.stereo_pairs.emplace_back(stereo_pairs.at(i), stereo_pairs.at(i + 1));
-    valid_stereo_pairs.push_back(stereo_pairs.at(i));
-    valid_stereo_pairs.push_back(stereo_pairs.at(i + 1));
-  }
-
-  // Calculate number of unique image camera image streams
-  params.state_options.num_unique_cameras = (int)params.stereo_pairs.size();
-  for (int i = 0; i < params.state_options.num_cameras; i++) {
-    if (std::find(valid_stereo_pairs.begin(), valid_stereo_pairs.end(), i) != valid_stereo_pairs.end())
-      continue;
-    params.state_options.num_unique_cameras++;
-  }
-
   // Set what representation we should be using
   std::transform(feat_rep_msckf_str.begin(), feat_rep_msckf_str.end(), feat_rep_msckf_str.begin(), ::toupper);
   std::transform(feat_rep_slam_str.begin(), feat_rep_slam_str.end(), feat_rep_slam_str.begin(), ::toupper);
@@ -235,6 +197,21 @@ VioManagerOptions parse_command_line_arguments(int argc, char **argv) {
     std::exit(EXIT_FAILURE);
   }
 
+  // Preprocessing histogram method
+  if (histogram_method_str == "NONE") {
+    params.histogram_method = TrackBase::NONE;
+  } else if (histogram_method_str == "HISTOGRAM") {
+    params.histogram_method = TrackBase::HISTOGRAM;
+  } else if (histogram_method_str == "CLAHE") {
+    params.histogram_method = TrackBase::CLAHE;
+  } else {
+    printf(RED "VioManager(): invalid feature histogram specified:\n" RESET);
+    printf(RED "\t- NONE\n" RESET);
+    printf(RED "\t- HISTOGRAM\n" RESET);
+    printf(RED "\t- CLAHE\n" RESET);
+    std::exit(EXIT_FAILURE);
+  }
+
   //====================================================================================
   //====================================================================================
   //====================================================================================
diff --git a/ov_msckf/src/utils/parse_ros.h b/ov_msckf/src/utils/parse_ros.h
index d8c05194d..1bfcac890 100644
--- a/ov_msckf/src/utils/parse_ros.h
+++ b/ov_msckf/src/utils/parse_ros.h
@@ -19,8 +19,7 @@
  * along with this program.  If not, see <https://www.gnu.org/licenses/>.
  */
 
-
-#if defined(ROS_AVAILABLE) || defined(DOXYGEN)
+#if ROS_AVAILABLE || defined(DOXYGEN)
 #ifndef OV_MSCKF_PARSE_ROSHANDLER_H
 #define OV_MSCKF_PARSE_ROSHANDLER_H
 
@@ -65,45 +64,6 @@ VioManagerOptions parse_ros_nodehandler(ros::NodeHandle &nh) {
     std::exit(EXIT_FAILURE);
   }
 
-  // Read in stereo pair information
-  std::vector<int> stereo_pairs;
-  nh.param<std::vector<int>>("stereo_pairs", stereo_pairs, stereo_pairs);
-  if (stereo_pairs.size() % 2 != 0) {
-    printf(RED "VioManager(): Specified number of stereo pair IDs needs to be even\n" RESET);
-    printf(RED "VioManager(): Example: (0,1,2,3) -> stereo tracking between 01 and 23\n" RESET);
-    std::exit(EXIT_FAILURE);
-  }
-  for (size_t i = 0; i < stereo_pairs.size(); i++) {
-    if (std::count(stereo_pairs.begin(), stereo_pairs.end(), stereo_pairs.at(i)) != 1) {
-      printf(RED "VioManager(): You can do stereo tracking between unique ids\n" RESET);
-      printf(RED "VioManager(): %d showed up multiple times\n" RESET, stereo_pairs.at(i));
-      std::exit(EXIT_FAILURE);
-    }
-    // if(stereo_pairs.at(i) >= params.state_options.num_cameras) {
-    //    printf(RED "VioManager(): Stereo pair has an id larger then the max camera\n" RESET);
-    //    printf(RED "VioManager(): %d is >= than %d\n" RESET,stereo_pairs.at(i),params.state_options.num_cameras);
-    //    std::exit(EXIT_FAILURE);
-    //}
-  }
-  std::vector<int> valid_stereo_pairs;
-  for (size_t i = 0; i < stereo_pairs.size(); i += 2) {
-    if (stereo_pairs.at(i) >= params.state_options.num_cameras || stereo_pairs.at(i + 1) >= params.state_options.num_cameras) {
-      printf(RED "ignoring invalid stereo pair: %d, %d\n" RESET, stereo_pairs.at(i), stereo_pairs.at(i + 1));
-      continue;
-    }
-    params.stereo_pairs.emplace_back(stereo_pairs.at(i), stereo_pairs.at(i + 1));
-    valid_stereo_pairs.push_back(stereo_pairs.at(i));
-    valid_stereo_pairs.push_back(stereo_pairs.at(i + 1));
-  }
-
-  // Calculate number of unique image camera image streams
-  params.state_options.num_unique_cameras = (int)params.stereo_pairs.size();
-  for (int i = 0; i < params.state_options.num_cameras; i++) {
-    if (std::find(valid_stereo_pairs.begin(), valid_stereo_pairs.end(), i) != valid_stereo_pairs.end())
-      continue;
-    params.state_options.num_unique_cameras++;
-  }
-
   // Read in what representation our feature is
   std::string feat_rep_msckf_str = "GLOBAL_3D";
   std::string feat_rep_slam_str = "GLOBAL_3D";
@@ -190,6 +150,39 @@ VioManagerOptions parse_ros_nodehandler(ros::NodeHandle &nh) {
   nh.param<int>("min_px_dist", params.min_px_dist, params.min_px_dist);
   nh.param<double>("knn_ratio", params.knn_ratio, params.knn_ratio);
 
+  // Preprocessing histogram method
+  std::string histogram_method_str = "HISTOGRAM";
+  nh.param<std::string>("histogram_method", histogram_method_str, histogram_method_str);
+  if (histogram_method_str == "NONE") {
+    params.histogram_method = TrackBase::NONE;
+  } else if (histogram_method_str == "HISTOGRAM") {
+    params.histogram_method = TrackBase::HISTOGRAM;
+  } else if (histogram_method_str == "CLAHE") {
+    params.histogram_method = TrackBase::CLAHE;
+  } else {
+    printf(RED "VioManager(): invalid feature histogram specified:\n" RESET);
+    printf(RED "\t- NONE\n" RESET);
+    printf(RED "\t- HISTOGRAM\n" RESET);
+    printf(RED "\t- CLAHE\n" RESET);
+    std::exit(EXIT_FAILURE);
+  }
+
+  // Feature mask
+  nh.param<bool>("use_mask", params.use_mask, params.use_mask);
+  for (int i = 0; i < params.state_options.num_cameras; i++) {
+    std::string mask_path;
+    nh.param<std::string>("mask" + std::to_string(i), mask_path, "");
+    if (params.use_mask) {
+      if (!boost::filesystem::exists(mask_path)) {
+        printf(RED "VioManager(): invalid mask path:\n" RESET);
+        printf(RED "\t- mask%d\n" RESET, i);
+        printf(RED "\t- %s\n" RESET, mask_path.c_str());
+        std::exit(EXIT_FAILURE);
+      }
+      params.masks.insert({i, cv::imread(mask_path, cv::IMREAD_GRAYSCALE)});
+    }
+  }
+
   // Feature initializer parameters
   nh.param<bool>("fi_triangulate_1d", params.featinit_options.triangulate_1d, params.featinit_options.triangulate_1d);
   nh.param<bool>("fi_refine_features", params.featinit_options.refine_features, params.featinit_options.refine_features);