Abstract
Multiple human tracking is an important research topic in computer vision. In the cluttered scene, an occlusion occurs frequently that makes the tracking problem even more challenging. In this thesis, we propose a tracking system to track each human object and solve the occlusion problem. We use color and motion, the two significant features, to distinguish and track different human objects. We classify each pixel to which human object it belongs by its relative position about an object and its color model. Therefore, each object region can be segmented effectively. Combining each object region and optical flow, we can track each object independently. When an occlusion happens, we analyze the color distribution of the occlusion group to differentiate each object in an occlusion. By calculating the distances between each objects, we can determine whether an object separate from the occlusion or not. For an object leaves an occlusion, we treat it as an individual and track it afterward.