Deep Ranking for Person Re-Identification via Joint Representation Learning

This paper proposes a novel approach to person re-identification, a fundamental task in distributed multi-camera surveillance systems. Although a variety of powerful algorithms have been presented in the past few years, most of them usually focus on designing hand-crafted features and learning metri...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 25; H. 5; S. 2353 - 2367
Hauptverfasser:	Chen, Shi-Zhe, Guo, Chun-Chao, Lai, Jian-Huang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Biometric Identification - methods Cameras Databases, Factual deep convolutional neural network Feature extraction Galleries Humans Image color analysis Learning learning to rank Machine Learning Measurement Neural networks Neural Networks (Computer) Person re-identification Probes Ranking Representations Similarity deep convolutional neural network Person re-identification learning to rank
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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