Probabilistic Integration of Tracking and Recognition of Soccer Players

This paper proposes a method for integrating player trajectories tracked in wide-angle images and identities by face and back-number recognition from images by a motion-controlled camera. In order to recover from tracking failures efficiently, the motion-controlled camera scans and follows players who are judged likely to undergo heavy occlusions several seconds in the future. The candidates of identities for each tracked trajectory are probabilistically modeled and updated at every identification. The degradation due to the passage of time and occlusions are also modeled. Experiments showed the system's feasibility for automatic real-time formation estimation which will be applied to metadata production with semantic and dynamic information on sports scenes.