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 extreme...

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Veröffentlicht in:IEEE transactions on image processing 2018-08, Vol.27 (8), p.3739-3752
Hauptverfasser: Cho, Yeong-Jun, Yoon, Kuk-Jin
Format: Artikel
Sprache:eng
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Zusammenfassung: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 pose-aware 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.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2018.2815840