Year: 2024
Type: article
Abstract: This study focuses on developing a system that uses state-of-the-art computer vision techniques to improve the accuracy and efficiency of table tennis tracking. The table tennis ball's trajectory and movement are tracked automatically by the system using a mobile camera array, allowing for real-time score updates without the need for human participation. This method guarantees precise and seamless scoring, freeing players from worrying about maintaining score and allowing them to concentrate fully on the game. The system uses player pose estimation technologies in addition to real-time scoring to track and record player positions and motions during the match. The system may provide a thorough study of player motions, including tracking posture and finding important motion patterns, by gathering and analyzing skeletal data.
Authors: Harsh Jain -, Aarsh Sharma -, Yadnyesh Thakare -, Dr. Pravin Shinde -, Prof. Bhagyashree Patil -, Dr. Nilakshi Jain -
Institution: University of Mumbai
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4402998152