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2015 | OriginalPaper | Chapter

Query Based Adaptive Re-ranking for Person Re-identification

Authors : Andy Jinhua Ma, Ping Li

Published in: Computer Vision -- ACCV 2014

Publisher: Springer International Publishing

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Abstract

Existing algorithms for person re-identification hardly model query variations across non-overlapping cameras. In this paper, we propose a query based adaptive re-ranking method to address this important issue. In our work, negative image pairs can be easily generated for each query under non-overlapping cameras. To infer query variations across cameras, nearest neighbors of the query positive match under two camera views are approximated and selected from positive matches in the training set. Locality preserving projections (LPP) are employed to ensure that each feature vector under one camera shares similar neighborhood structure with the corresponding positive match. Using existing re-identification algorithms as base score function, the optimal adaptive model is learnt by least-square regression with manifold regularization. Experimental results show that the proposed method can improve the ranking performance and outperforms other adaptive methods.

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Title: Query Based Adaptive Re-ranking for Person Re-identification
Authors: Andy Jinhua Ma
Ping Li
Publisher: Springer International Publishing
Book: Computer Vision -- ACCV 2014
Print ISBN: 978-3-319-16813-5

Electronic ISBN: 978-3-319-16814-2

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-3-319-16814-2_26

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