PaMM: Pose-aware Multi-shot Matching for Improving Person Re-identification

Person re-identification is the problem of recognizing people across different images or videos with non-overlapping views. Although a significant progress has been made in person re-identification over the last decade, it remains a challenging task because the appearances of people can seem extremely different across diverse camera viewpoints and person poses. In this paper, we propose a novel framework for person re-identification by analyzing camera viewpoints and person poses called poseaware multi-shot matching. It robustly estimates individual poses and efficiently performs multi-shot matching based on the pose information. The experimental results obtained by using public person re-identification data sets show that the proposed methods outperform the current state-of-the-art methods, and are promising for accomplishing person re-identification under diverse viewpoints and pose variances.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2018-08
Language
English
Article Type
Article
Keywords

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Citation

IEEE TRANSACTIONS ON IMAGE PROCESSING, v.27, no.8, pp.3739 - 3752

ISSN
1057-7149
DOI
10.1109/TIP.2018.2815840
URI
http://hdl.handle.net/10203/242220
Appears in Collection
ME-Journal Papers(저널논문)
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