Anti-occlusion observation model and automatic recovery for multi-view ball tracking in sports analysis

Abstract

The 3D position of the ball plays a crucial role in professional sport analysis. In ball sports, tracking of ball's precise position accurately is highly required, whose performance is affected by inaccurate 3D coordinates and occlusion problem. In this paper, we propose anti-occlusion observation model and automatic recovery by 3D ball detection based on multiview videos to track the ball in 3D space. The anti-occlusion observation model evaluates each camera's image and eliminates the influence of the cameras in which the ball is occluded. The automatic recovery method detects the ball's 3D position by homography relation of the multi-video and generates a new distribution to initiate the tracker when tracking failure is detected. Experimental results based on the HDTV video sequences, which were captured by four cameras located at the corners of the court, show that the success rate of the 3D ball tracking achieves 99.14%.