Human Body Segmentation in the Presence of Occlusion

Bi Sheng, Xiaoyan Shen, Qiang Wang
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Abstract

Human body segmentation in complex situation is an important processing stage in video surveillance. The results have great affects on tracking, behavior recognition or object identification. In this paper, we present a method to segment region in which human bodies are overlapping or walking together. The multiple human objects region is segmented using potential function clustering in the vertical projection histograms of the region, the segmented results are verified by analyzing their geometry features. If the results are not consistent with the human geometry feature, it shows that multiple humans are overlapping. A binocular vision algorithm is proposed to segment the region based on distance. The Experimental results prove the algorithm works robustly, adaptively and efficiently.
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遮挡存在下的人体分割
复杂情况下的人体分割是视频监控中的一个重要处理阶段。结果对跟踪、行为识别或目标识别都有很大的影响。在本文中,我们提出了一种分割人体重叠或一起行走区域的方法。在区域的垂直投影直方图中利用势函数聚类对多人体目标区域进行分割,并通过分析其几何特征对分割结果进行验证。如果结果与人体几何特征不一致,则说明多个人体重叠。提出了一种基于距离的双目视觉区域分割算法。实验结果证明了该算法的鲁棒性、自适应性和有效性。
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