Depth assisted Tracking Multiple Moving Objects under Occlusion

نویسندگان

  • Anh Tu Tran
  • Koichi Harada
چکیده

In this paper, we have presented a novel tracking method aiming at detecting objects and maintaining their label/identification over the time. The main key factors of this method are to use depth information and different strategies to track objects under various occlusion scenarios. The foreground objects are detected and refined by background subtraction and shadow cancellation. The occlusion detection is based on information of foreground blobs in successive frames. The occlusion regions are projected to the projection plane XZ to analysis occlusion situation. According to the occlusion analysis results, different objects correspondence strategies are introduced to track object under various occlusion scenarios including tracking occluded objects in similar depth layer and in different depth layers. The experimental results show that our proposed method can track the moving objects under the most typical and challenging occlusion scenarios.

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تاریخ انتشار 2013