Indirect Person Re-identification Based on Support Samples
SUN Rui①② FANG Wei①② HUANG Qiheng①② GAO Jun①
①(School of Computer and Information, Hefei University of Technology, Hefei 230009, China) ②(Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230009, China)
Abstract：Person re-identification is the identification of the same pedestrian in a multi camera surveillance without overlapping views. Aiming at the problem of the existence of visual angle, illumination and scale change in pedestrian images which from different camera. An indirect person re-identification method is proposed based on the support samples. At first, the algorithm extracts the support samples from different cameras by the clustering method. When it comes to matching pedestrians from different cameras, the support samples are used to distinguish the pedestrians categories under the camera on the basis of the distance metric, by comparing the categories to determine whether the same pedestrian. The method avoids the direct matching of pedestrian images under different cameras, which effectively solve the problem of the existence of visual angle, illumination and scale change in different camera. The experimental results show that the algorithm has a high recognition rate, and on the data set VIPeR, CAVIAR4ReID and CUHK01the, Rank1 reaches 43.60%, 41.36% and 43.82% respectively.
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.
SUN Rui, FANG Wei, HUANG Qiheng, GAO Jun. Indirect Person Re-identification Based on Support Samples. JEIT, 2017, 39(12): 2953-2961.
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