This project attempts to implement the Lucas-Kanade object tracking algorithm. Given three videos (2 cars and 1 helicopter landing site) as input, the tracking algorithm is supposed to output a bounding box over the cars/helicopter landing site for every frame throughout the video. A template is defined by drawing a bounding box around the object to be tracked in the first frame of the video. Then, for each of the subsequent frames the tracker will update an affine transform that warps the current frame so that the template in the first frame is aligned with the warped current frame.
This project was developed as part of the course Computer Vision in the Fall 2022 semester at the Faculty of Engineering, Alexandria University, under the Computer and Communications Engineering department, supervised by Dr. Marwan Torki. Note: this project is yet to be finished.
The original videos can be found here, in the form of .npy files.
This project was developed in the following environment:
- Jupyter Notebook
- Miniconda
- Python 3.11.5
1- Clone the repository to your local machine:
git clone https://github.com/MohEsmail143/lucas-kanade-object-tracker.git2- Open Jupyter notebook.
3- Check out the the Jupyter notebook object_tracking_in_videos.ipynb.
This project is licensed under the MIT License - see the LICENSE.md file for details.