This repository is C++ OpenCV implementation of Stereo Visual Odometry, using OpenCV calcOpticalFlowPyrLK for feature tracking.
Reference Paper: https://lamor.fer.hr/images/50020776/Cvisic2017.pdf
Demo vedio: https://www.youtube.com/watch?v=Z3S5J_BHQVw&t=17s
Tested on KITTI odometry dataset
git clone https://github.com/ZhenghaoFei/visual_odom.git
The system use Camera Parameters in calibration/xx.yaml, put your own camera parameters in the same format and pass the path when you run.
mkdir build
cd build
cmake ..
make -j4
./run /PathToKITTI/sequences/00/ ../calibration/kitti00.yaml
Thanks to temburuyk, the most time consumtion function circularMatching() can be accelerated using CUDA and greately improve the performance.
To enable GPU acceleration
- Make sure you have CUDA compatible GPU.
- Install CUDA, compile and install CUDA supported OpenCV
- Change gpu_build to 1 in /src/feature.h
- Compile & Run