CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
From Groups to Co-traveler Sets: Pair Matching based Person Re-identification Framework
Cao, Min1,3; Chen, Chen1; Hu, Xiyuan1,3; Peng, Silong1,2,3
2017-10
Conference NameInternational Conference on Computer Vision Workshop
Conference Date2017-10
Conference PlaceVenice, Italy
AbstractIn video surveillance, group refers to a set of people with similar velocity and close proximity. Group members can provide visual clues for person re-identification. In this paper, we discuss the essentials of group-based person re-identification and relax the group definition towards a concept of “co-traveler set”, keeping constraints on velocity differences while loosening the distance constraint. Accordingly we propose a pair matching scheme to measure the distance between co-traveler sets, which tackles the problems caused by dynamic change of group across camera views. The final individual matching score is weighted by the obtained distance measurements between co-traveler sets. A proof of concept shows the rationality of introducing the concept of co-traveler relation into person reid. Experiments were conducted on four different datasets. Our co-traveler set based framework shows promising improvement compared with the group-based methods and the individual-based methods.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19686
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorChen, Chen
Affiliation1.Institute of Automation Chinese Academy of Sciences Beijing
2.Beijing Visytem Co. Ltd
3.University of Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Cao, Min,Chen, Chen,Hu, Xiyuan,et al. From Groups to Co-traveler Sets: Pair Matching based Person Re-identification Framework[C],2017.
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