Simultaneous physical and conceptual ball state estimation in volleyball game analysis

Automatically extraction of accurate volleyball game data from game videos plays an important role in making contribution to game data analysis, TV broadcasting and performance evaluations. In this paper, a particle filter based physical and conceptual ball state estimation method is proposed to track the 3D ball trajectory and ball event simultaneously with high accuracy. The physical ball state includes 3D ball position and velocity. Besides the ball event, the conceptual state also includes flag of the external force on the ball. The system model is adaptive to this external force predicted through proposed spatial hitting points dense distribution. Observation of the external force is evaluated by hitting point likelihood, which uses not only the past tracked trajectory but also the image noise feature so that image noise is transferred into useful feature and unidirectional dependency on trajectory is avoided. Experimental results based on multi-view HDTV video sequences show the tracking success rate of ball state achieves 92.43%.