Stereo Visual Odometry

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

Requirements

OpenCV 3.0

Dataset

Tested on KITTI odometry dataset

Compile & Run

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

GPU CUDA acceleration

The most time consumtion function circularMatching() can be accelerated using CUDA and greately improve the performance.
To enable GPU acceleration

1. Make sure you have CUDA compatible GPU.
2. Install CUDA, compile and install CUDA supported OpenCV
3. When compiling, use

cmake .. -DUSE_CUDA=on

4. Compile & Run

ROS Integration

The ros_cuda branch has ros integration which publishes the final pose as geometry_msgs::PoseStamped and path as nav_msgs::Path .

Reference code

1. Monocular visual odometry algorithm

2. Matlab implementation of SOFT