Abstract 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.
Pseudo Measurement Based Multiple Model Approach for Robust Player Tracking
Computer Vision – ACCV 2006 ; 7 ; 781-790
Lecture Notes in Computer Science ; 3852 , 7
2006-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Multiple Model , Target Representation , Appearance Information , Shift Procedure , Player Localization Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity
Pseudo Measurement Based Multiple Model Approach for Robust Player Tracking
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