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| A Statistical Inference Approach for Person Re-identification |
| Du Yu-ning Ai Hai-zhou |
| Computer Science and Technology Department, Tsinghua University, Beijing 100084, China |
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Abstract Person re-identification, identifying the same person’s images in an existing database come from non-overlapping camera views, is a valuable but challenging task. This paper proposes a statistical inference approach for person re-identification. A similarity measure of two person images is learned from a statistical inference perspective. Then the similarity measure is utilized to query a person from a gallery set. The proposed approach is demonstrated on VIPeR dataset, and the experiment shows that it outperforms the state-of-the-art approaches. Besides, it costs less time than the existing learning-based ones in training, and alleviates the over-fitting problem when there are few training data.
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Received: 30 July 2013
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Corresponding Authors:
Du Yu-ning
E-mail: dyn10@mails.tsinghua.edu.cn
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2014, Vol. 36 
