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 | |
会议名称 | International Conference on Computer Vision Workshop on Cross-domain Human Identification (ICCVW) |
会议日期 | 2017-10 |
会议地点 | Venice, Italy |
摘要 | 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. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19686 |
专题 | 智能制造技术与系统研究中心_多维数据分析(彭思龙)-技术团队 |
通讯作者 | Chen, Chen |
作者单位 | 1.Institute of Automation Chinese Academy of Sciences Beijing 2.University of Chinese Academy of Sciences 3.Beijing Visytem Co. Ltd |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 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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