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基于支持样本间接式的行人再识别

孙锐 方蔚 黄启恒 高隽

孙锐, 方蔚, 黄启恒, 高隽. 基于支持样本间接式的行人再识别[J]. 电子与信息学报, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215
引用本文: 孙锐, 方蔚, 黄启恒, 高隽. 基于支持样本间接式的行人再识别[J]. 电子与信息学报, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215
SUN Rui, FANG Wei, HUANG Qiheng, GAO Jun. Indirect Person Re-identification Based on Support Samples[J]. Journal of Electronics and Information Technology, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215
Citation: SUN Rui, FANG Wei, HUANG Qiheng, GAO Jun. Indirect Person Re-identification Based on Support Samples[J]. Journal of Electronics and Information Technology, 2017, 39(12): 2953-2961. doi: 10.11999/JEIT170215

基于支持样本间接式的行人再识别

doi: 10.11999/JEIT170215
基金项目: 

国家自然科学基金(61471154),安徽省科技攻关科技强警项目(170d0802181)

Indirect Person Re-identification Based on Support Samples

Funds: 

The National Natural Science Foundation of China (61471154), Anhui Province Science and Technology Research (170d0802181)

  • 摘要: 行人再识别就是在无重叠视域多摄像机监控系统中,识别出相同的行人。针对来自于不同摄像头行人图片存在着视角、光照和尺度变化的问题。该文提出了基于支持样本间接式匹配的行人再识别方法。该算法首先通过聚类的方法分别提取不同摄像头下的支持样本,当要对来自不同摄像头的行人进行匹配时,在距离测度的基础上利用支持样本分别判别出其所在摄像头下的行人类别,通过类别的对比判断是否为同一行人。该方法避免了不同摄像头下行人图片直接匹配,有效解决不同摄像头带来的视角、光照和尺度问题。实验结果表明该文的算法相比一些经典算法识别率有一定的提高,并且在数据集VIPeR, CAVIAR4ReID和CUHK01上,Rank1分别达到了43.60%, 41.36%, 43.82%。
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    出版历程
    • 收稿日期:  2017-03-17
    • 修回日期:  2017-09-15
    • 刊出日期:  2017-12-19

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