Game-theoretical occlusion handling for multi-target visual tracking

Multi-target visual tracking is a challenge because of data association and mutual occlusion in the interacting targets. This paper presents a Gaussian mixture probability hypothesis density based multi-target visual tracking system with game-theoretical occlusion handling. Firstly, the spatial constraint based appearance model with other interacting targets’ interferences is modeled. Then, a two-step occlusion reasoning algorithm is proposed. Finally, an n-person, non-zero-sum, non-cooperative game is constructed to handle the mutual occlusion problem. The individual targets within the occlusion region are regarded as the players in the constructed game to compete for the maximum utilities by using the certain strategies. A Nash Equilibrium of the game is the optimal estimation of the locations of the players within the occlusion region. Experiments on video sequences demonstrate the good performance of the proposed occlusion handling algorithm.