This is an OpenCV 3.0 based implementation of a monocular visual odometry algorithm.

Algorithm

Uses Nister's Five Point Algorithm for Essential Matrix estimation, and FAST features, with a KLT tracker. More details are available here as a report, and here as a blog post.

Note that this project is not yet capable of doing reliable relative scale estimation, so the scale informaion is extracted from the KITTI dataset ground truth files.

NOTE: This repository was forked from Avi Singh's github account

Demo Video

Click on the GIF/Image to go to the full youtube video.

1. Small Dataset

2. Larger Dataset

Requirements

OpenCV 4.0 or above

How to compile?

Provided with this repo is a CMakeLists.txt file, which you can use to directly compile the code as follows:

mkdir build
cd build
cmake ..
make

How to run?

After compilation, in the build directly, type the following:

./vo

Before you run

In order to run this algorithm, you need to have either your own data, or else the sequences from KITTI's Visual Odometry Dataset. In order to run this algorithm on your own data, you must modify the intrinsic calibration parameters in the code.

Contact

For any queries, contact: [email protected]

License

MIT