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This paper presents a solution to the problem of tracking people within crowded scenes. The aim is to maintain individual object identity through a crowded scene which contains complex interactions and heavy occlusions of people. Our approach uses the strengths of two separate methods; a global object detector and a localised frame by frame tracker. A temporal relationship model of torso detections built during low activity period, is used to further disambiguate during periods of highdoi:10.1007/978-3-540-75703-0_12 dblp:conf/humo/GilbertB07 fatcat:77nnozj2kng5tmwroxyzikytry