Contrast Maximization for Event-based Cameras

Project Overview

The Contrast Maximization method plays a pivotal role in event-based vision applications, offering innovative solutions for challenges like motion, depth, and optical flow estimation. Despite its importance, there hasn't been an accessible open-source implementation available online.

To empower the research community working with event-based cameras, I've created this repository featuring an efficient implementation of the Contrast Maximization framework.

Contrast Maximization for Estimating Camera 3D Rotation

 

Contrast Maximization for Estimating 2D Translation

 

Key Features

• High Efficiency: Utilizing the Ceres solver for optimization and parallel computation, this implementation delivers a highly efficient solution, achieving near real-time performance under certain conditions.

• Flexible Applications: The repository is built on ROS, making it straightforward to compile, run, and integrate into other projects. We also provide test data to facilitate easy testing.

Citation

This project is part of our research paper. If you find this repository useful for your academic projects, please consider citing our paper and the original Contrast Maximization paper.

@article{xing2023target,
  title={Target-free Extrinsic Calibration of Event-LiDAR Dyad using Edge Correspondences},
  author={Xing, Wanli and Lin, Shijie and Yang, Lei and Pan, Jia},
  journal={IEEE Robotics and Automation Letters},
  year={2023},
  publisher={IEEE}
}

Usage Guide

Here's how you can start using this repository for your research or projects:

1. Clone the Repository

Begin by cloning the repository into your ROS workspace:

cd ~/catkin_ws/src
git clone https://github.com/FORREST1901/contrast-maximization-for-event-cameras.git

2. Install Dependencies

This project relies primarily on the following packages:

• Ceres Solver: Follow the installation guide.
• dv-ros: Install from the inivation/dv-ros GitLab repository.

3. Build the Project

After the dependencies are installed, build the ROS workspace:

cd ~/catkin_ws
catkin_make

4. Download Test Data

Download the dataset via the OneDrive link. Place the data files in the /data folder within the project directory:

mkdir -p ~/catkin_ws/src/contrast-maximization-for-event-cameras/data
mv <downloaded-data> ~/catkin_ws/src/contrast-maximization-for-event-cameras/data

5. Launch and Run

Use the provided ROS launch files to start the framework:

• For 2D translation:

roslaunch contrast_maximization cm_translation_2d.launch

• For 3D rotation:

roslaunch contrast_maximization cm_rotation_3d.launch

Contact

For further questions or support, please reach out to us at [[email protected]].

Thank you for your interest in our research!