An Automated Tracking System for Locating Impact Points on a Table Tennis Surface Using Ping Pong Balls
This project presents a novel system for real-time table tennis ball tracking and hitting point prediction, developed using OpenCV-Python.The system is designed to contribute to strategic analysis in the sport by accurately identifying the ball's trajectory and anticipating its landing point.The proposed system is comprised of four key modules: ball detection, ball tracking, hitting point prediction, and data visualization.Computer vision techniques are employed to effectively detect and monitor the ball's movement.Kalman filtering is utilized to refine the prediction of the ball's landing point.The generated data is then presented visually to facilitate analysis and comprehension of game dynamics.
Authors
- Wei Hong Lim (ORCID: https://orcid.org/0000-0003-1673-8088)
- Moona Mazher (ORCID: https://orcid.org/0000-0003-4444-5776)
- Sanjoy Kumar Debnath (ORCID: https://orcid.org/0000-0002-5019-3897)
- M.K.A. Ahamed Khan (ORCID: https://orcid.org/0000-0002-1863-3354)
- Abdul Qayyum (ORCID: https://orcid.org/0000-0003-3102-1595)
- Miad Mokayef
- Wai Kit Lee (ORCID: https://orcid.org/0000-0001-9149-7347)
- Sew Sun Tiang (ORCID: https://orcid.org/0000-0001-8433-8663)
- Mastaneh Mokayef (ORCID: https://orcid.org/0000-0002-8806-7749)
- MHD Amen Summakieh
- Takao Ito
Institutions
- Hiroshima University (JP)
- University College London (GB)
- Imperial College London (GB)
- UCSI University (MY)
- Chitkara University (IN)
Publication Details
- Journal
- Proceedings of International Conference on Artificial Life and Robotics
- Published
- 2025-02-13
- DOI
- https://doi.org/10.5954/icarob.2025.os25-2
- Primary Topic
- Sports Dynamics and Biomechanics
- Type
- article
- Field-Weighted Citation Impact
- 0.00