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Dependence-Aware Feature Coding for Person Re-Identification

delete2018-04-01
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PRE
AI
X
Xiaobo Wang
Z
Zhen Lei *
S
Shengcai Liao
X
Xiaojie Guo
Y
Yang Yang
S
Stan Z. Li
DOI:10.1109/LSP.2018.2803776delete
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Abstract

Abstract

En 中文
In this letter, we focus on how to boost the performance of person re-identification by exploring the discriminative information among person pairs. A novel dependence-aware feature coding framework is proposed for this task. Specifically, we employ theHilbert-Schmidt independence criterion as the discriminative term, which is to explore the dependence between different kinds of person pairs, i.e., the same person pairs should be dependence maximized, while the different ones should be dependence minimized. Theoretical discussion and analysis on the convexity of the proposed constraint, as well as the convergence of our algorithm, are provided. Experimental results on two benchmark datasets have demonstrated the advantages of our method over the state-of-the-art alternatives.
Keywords:
Feature coding
Person re-identification
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Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

I
institute of automation, cas
Scholars:
2.2K
Papers: 2.1K
Citations: 2
C
chinese academy of sciences
Scholars:
56.3W
Papers: 44.8W
Citations: 704