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2016 | OriginalPaper | Buchkapitel

Adaptive Multi-Metric Fusion for Person Re-identification

verfasst von : Penglin Li, Mengxue Liu, Yun Gu, Lixiu Yao, Jie Yang

Erschienen in: Pattern Recognition

Verlag: Springer Singapore

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Abstract

Person re-identification, which aims at recognizing a person of interest across spatially disjoint camera views, is still a challenging task. Plenty of approaches emerge in recent years and some of them achieve good matching results. Given a probe image, we observe that the ranking results generated by different approaches differ from each other. Considering these conventional methods are reasonable, we propose an Adaptive Multi-Metric Fusion (AMMF) method which fuses the existing ranking results with query-specific weights. Experiments on two challenging databases, VIPeR and ETHZ, demonstrate that the proposed method achieves further performance improvement.

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Metadaten
Titel
Adaptive Multi-Metric Fusion for Person Re-identification
verfasst von
Penglin Li
Mengxue Liu
Yun Gu
Lixiu Yao
Jie Yang
Copyright-Jahr
2016
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-3002-4_22

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