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文章基本信息

  • 标题:Depth assisted Tracking Multiple Moving Objects under Occlusion
  • 本地全文:下载
  • 作者:Anh Tu Tran ; Koichi Harada
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2013
  • 卷号:13
  • 期号:5
  • 页码:49-56
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要: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.
  • 关键词:Visual tracking; multiple object tracking; stereo tracking; occlusion analysis.
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