Subject Centric Group Feature for Person Re-Identification

Li Wei, Shishir K. Shah; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2015, pp. 28-35

Abstract


This paper presents a subject centric group feature for person re-identification. Our approach is inspired by the observation that people often tend to walk alongside others or in a group. We argue that co-travelers' information, including geometry and visual cues, can reduce the re-identification ambiguity and lead to better accuracy, compared to approaches that rely only on visual cues. We introduce person-group feature to capture both geometry and visual information of co-travelers around a subject. We compute the dis-similarity between person-group features by solving an integer programming problem. The proposed approach is evaluated in its ability to improve the accuracy of re-identification of people traveling within groups. The results show that our approach outperforms state-of-the-art visual based as well as group information based methods.

Related Material


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[bibtex]
@InProceedings{Wei_2015_CVPR_Workshops,
author = {Wei, Li and Shah, Shishir K.},
title = {Subject Centric Group Feature for Person Re-Identification},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2015}
}