Abstract
Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes) for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.
Highlights
Multiple-view multiple-object tracking has become an essential technology for many applications such as video surveillance system
This paper proposes a novel method for multiple human tracking in multiple views
This paper presents the so-called multiview-based cooperative tracking system by using particle filter
Summary
Multiple-view multiple-object tracking has become an essential technology for many applications such as video surveillance system. Different from other multiview-based works on multiple targets tracking [14,15,16,17,18,19,20,21], this paper aims at solving the occlusion problem by combining the multiple camera inputs. This approach is based on the concepts of data sharing and resource sharing of the tracking processes for all the targets. In comparison with the other multiview noncooperative tracking methods [14,15,16,17,18,19,20,21], our method can track the objects more effectively
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