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, Min1,2; Chen, Chen1,2; Hu, Xiyuan1,2; Peng, Silong1,2,3
2017-10
Conference NameInternational Conference on Computer Vision Workshop on Cross-domain Human Identification (ICCVW)
Conference Date2017-10
Conference PlaceVenice, Italy
Abstract

In 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.University of Chinese Academy of Sciences
3.Beijing Visytem Co. Ltd
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, 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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