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Person re-identification with fusion of hand-crafted and deep pose-based body region features
[article]
2018
arXiv
pre-print
Person re-identification (re-ID) aims to accurately re- trieve a person from a large-scale database of images cap- tured across multiple cameras. Existing works learn deep representations using a large training subset of unique per- sons. However, identifying unseen persons is critical for a good re-ID algorithm. Moreover, the misalignment be- tween person crops to detection errors or pose variations leads to poor feature matching. In this work, we present a fusion of handcrafted features and
arXiv:1803.10630v1
fatcat:3fnnkry7qnamlng66kxpsg5jiy