Fast moving table tennis ball tracking algorithm based on graph neural network.

The key object tracking in sports video scenarios poses a pivotal challenge in the analysis of sports techniques and tactics. In table tennis, due to the small size and rapid motion of the ball, identifying and tracking the table tennis ball through video is a particularly arduous task, where the majority of existing detection and tracking algorithms struggle to meet the practical application requirements in real-world scenarios. To address this issue, this paper proposes a combined technical approach integrating detection and discrimination, tailored to the unique motion characteristics of table tennis.