Tracking　humans　in　video　is　a　challenge　because　of　data　association　and　mutual　occlusion　problems.　This　paper　presents　a　Gaussian　mixture　probability　hypothesis　density-based　visual　tracking　system　with　game-theoretical　occlusion　handling.　First,　a　two-step　occlusion　reasoning　algorithm　is　proposed　to　determine　the　occlusion　region.　Then,　an　improved　spatial　color　appearance　with　interferences　by　other　targets　within　the　occlusion　region　is　modeled.　Finally,　an　n-person,　non-zero-sum,　non-cooperative　game　is　constructed　to　bridge　the　joint　measurements　estimation　and　the　game.　The　individual　measurements　within　the　occlusion　region　are　regarded　as　the　players　in　the　constructed　game　competing　for　maximum　utilities　using　certain　strategies.　The　Nash　equilibrium　of　the　game　is　the　optimal　estimations　of　the　locations　of　the　players　within　the　occlusion　region.　Experiments　conducted　on　publicly　available　videos　demonstrate　the　good　performance　of　the　proposed　occlusion　handling　algorithm.