E. Parvizi and Q. M. J. Wu, “Multiple Object Tracking Based on Adaptive Depth Segmentation,” Canadian Conference on Computer and Robot Vision, Windsor, 28-30 May 2008, pp. 273-277.

has been cited by the following article:

• TITLE: Depth-Aided Tracking Multiple Objects under Occlusion

  AUTHORS: Anh Tu Tran, Koichi Harada

  KEYWORDS: Visual Tracking; Multiple Object Tracking; Stereo Tracking; Occlusion Analysis

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.4 No.3, August 15, 2013

  ABSTRACT: In this paper, we have presented a novel tracking method aiming at detecting objects and maintaining their la-bel/identification over the time. The 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’ corresponding strategies are introduced to track objects 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.