In this paper, we propose an effective multi-object tracking system which can handle the partial occlusion in the tracking process. First, this method employs the part-based model to localize the person and body parts in every frame. Then it leverages the motion characteristics of both parts and the entire body to generate the trajectories of individuals. To overcome the difficulty in partial occlusion, we propose to formulate the task of multi-object tracking into multi-object matching with body part cues. The large scale comparison experiment on the popular tracking datasets demonstrates the superiority of the proposed method.
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