Pseudo Measurement Based Multiple Model Approach for Robust Player Tracking

This paper presents a robust player tracking method for sports video analysis. In order to track agile player stably and robustly, we employ multiple models method, with a mean shift procedure corresponding to each model for player localization. Furthermore, we define pseudo measurement via fusing the measurements obtained by mean shift procedure. And the fusing coefficients are built from two likelihood functions: one is image based likelihood; the other is motion based association probability. Experimental results show effectiveness of our method in the hard case of player tracking literature.