Project developed by Paolo Riva, Michelangelo Stasi, Mihai-Viorel Grecu c/o Politecnico di Milano Course: Image Analysis and Computer Vison - A.A. 2023/24 This Computer Vision project aims at detecting data in a tennis match through the widely-used Human Pose Detection method and the TRACE methon for ball detection.
The program focuses specifically on the following tasks: 0. Identify the field lines and, knowing the field measures, find yhe homography H from field to image.
- Use the well-known Human Pose Estimation method (based on Deep Learning) to identify the articulated segments of the player.
- Select the feet (end points of the leg segments) and their position Pleft and Pright in each image
- Check whether the feet are static or they are moving (by checking if H^-1 Pleft and/or H^-1 Pright are constant along a short sequence). If a foot is static, assume that it is placed on the ground.
- Collect the time-sequence of the step points: i.e., the positions H^-1P of the feet in the instances when they were static.
- In parallel, try to select the time instants when the player hits the ball with the rackets, and try to compute statistics on the short runs between consecutive hits
pip install -r requirements.txt
*/main.py [video_path.mp4]