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.