标题:Crowd motion segmentation via streak flow and collectiveness
作者:Gao, Ming-Liang ;Wang, Yi-Ting ;Jiang, Jun ;Shen, Jin ;Zou, Guo-Feng ;Liu, Li-Na
作者机构:[Gao, Ming-Liang ;Shen, Jin ;Zou, Guo-Feng ;Liu, Li-Na ] School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, Chi 更多
会议名称:2017 Chinese Automation Congress, CAC 2017
会议日期:October 20, 2017 - October 22, 2017
来源:Proceedings - 2017 Chinese Automation Congress, CAC 2017
出版年:2017
卷:2017-January
页码:4067-4070
DOI:10.1109/CAC.2017.8243492
摘要:Crowd motion segmentation problem is a hot issue in crowd behavior analysis and action recognition. A number of methods have been proposed to tackle this problem. Among the existing methods, most used flow dynamics to model the crowd motion, with only a few taking the collective property into consideration. In this paper, we proposed a crowd motion segmentation approach based on streak flow and crowd collectiveness, where the streak flow is adopted to reveal the dynamical property of crowd motion, and the collectiveness is incorporated to reveal the structure property. Experimental results show that our method can offer better segmentation accuracy than the state-of-the-art methods on the benchmark dataset.
© 2017 IEEE.
收录类别:EI
资源类型:会议论文
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