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.　©　2013　Elsevier　Ltd.　All　rights　reserved.