Tracking　multiple　moving　targets　in　video　is　still　a　challenge　because　of　mutual　occlusion　problem.　This　paper　presents　a　Gaussian　mixture　probability　hypothesis　density-based　visual　tracking　system　with　game　theory-based　mutual　occlusion　handling.　First,　a　two-step　occlusion　reasoning　algorithm　is　proposed　to　determine　the　occlusion　region.　Then,　the　spatial　constraint-based　appearance　model　with　other　interacting　targets¶　interferences　is　modeled.　Finally,　an　n-person,　non-zero-sum,　non-cooperative　game　is　constructed　to　handle　the　mutual　occlusion　problem.　The　individual　measurements　within　the　occlusion　region　are　regarded　as　the　players　in　the　constructed　game　competing　for　the　maximum　utilities　by　using　the　certain　strategies.　The　Nash　Equilibrium　of　the　game　is　the　optimal　estimation　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.　©　2013　IEEE.