Motion Prejudgment Dependent Mixture System Noise in System Model for Tennis Ball 3D Position Tracking by Particle Filter

In tennis game analysis, the 3D position of ball plays a crucial role in score judgment and player evaluation. When tracking the tennis ball in 3D space, high speed and abrupt motion change of the tennis ball are the main problems which make it difficult to predict the near future course of the ball. Aiming at solving above two problems, we propose a system model based on an elaborated mixture system noise. The mixture system noise consists of general change noise and adaptive abrupt change noise which is dependent on motion prejudgment result of tennis ball. The motion prejudgment method is carried out by the current state of ball and players. The motion of ball is classified into general motion and three abrupt motions, including smash, bounce and hit the net. Experiments based on 13 HDTV video sequences, which were recorded by four cameras located at four corners of the tennis court outside in a cloudy day including two players were used to explore the performance of the proposed method. The tracking success rate is 81.14%, gaining 27.64% improvement compared with conventional work.