Abstract.

We address the problem of robust multi-target tracking within the application of hockey player tracking. The particle filter tech- nique is adopted and modified to fit into the multi-target tracking frame- work. A rectification technique is employed to find the correspondence between the video frame coordinates and the standard hockey rink co- ordinates so that the system can compensate for camera motion and improve the dynamics of the players. A global nearest neighbor data association algorithm is introduced to assign boosting detections to the existing tracks for the proposal distribution in particle filters. The mean- shift algorithm is embedded into the particle filter framework to stabilize the tra jectories of the targets for robust tracking during mutual occlu- sion. Experimental results show that our system is able to automatically and robustly track a variable number of targets and correctly main- tain their identities regardless of background clutter, camera motion and frequent mutual occlusion between targets.