Key Person Aided Re-identification in Partially Ordered Pedestrian Set | |
Chen Chen1; Min Cao1; XiYuan Hu1; Silong Peng1 | |
2017 | |
会议名称 | the British Machine Vision Conference (BMVC) 2017 |
会议日期 | 2017-09-04 |
会议地点 | London, UK |
摘要 | Ideally person re-identification seeks for perfect feature representation and metric model that re-identify all various pedestrians well in non-overlapping views at different locations with different camera configurations, which is very challenging. However, in most pedestrian sets, there always are some outstanding persons who are relatively easy to re-identify. Inspired by the existence of such data division, we propose a novel key person aided person re-identification framework based on the re-defined partially ordered pedestrian sets. The outstanding persons, namely “key persons”, are selected by the K-nearest neighbor based saliency measurement. The partial order defined by pedestrian entering time in surveillance associates the key persons with the query person temporally and helps to locate the possible candidates. Experiments conducted on two video datasets show that the proposed key person aided framework outperforms the state-of-the-art methods and improves the matching accuracy greatly at all ranks. |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19679 |
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, China 2.University of Chinese Academy of Sciences, Beijing, China 3.Beijing ViSystem Corporation Limited, China |
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 | Chen Chen,Min Cao,XiYuan Hu,et al. Key Person Aided Re-identification in Partially Ordered Pedestrian Set[C],2017. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Chen_2017_BMVC.pdf(10740KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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