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| Person Re-identification Based on Regularization of Independent Measure Matrix |
| QI Meibin, WANG Yunxia, TAN Shengshun, LIU Hao, JIANG Jianguo |
| School of Computer and Information, Hefei University of Technology, Hefei 230009 |
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Abstract To solve the over-fitting problem caused by less training samples in the current person re-identification method based on distance metric learning, a person re-identification algorithm based on regularization of independent measure matrix is proposed. Firstly, the features extracted from four different color spaces are used to learn four different measure matrices. Then, the corresponding matrixes are regularized respectively, and the similarity of testing examples is measured by the regularized matrices. Finally, the final similarity is obtained by fusing results of the similarity measure. Experimental results show the improvement of the proposed method in performance for the over-fitting problem caused by less training samples.
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Received: 27 August 2015
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Corresponding Authors:
WANG Yunxia(Corresponding author), born in 1991, master student. Her research interests include person re-identification.
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| About author:: QI Minbin, born in 1969, Ph.D., professor. His research interests include intelligent video surveillance and DSP technology and its application.(TAN Shengshun, born in 1990, master student. His research interests include object retrieval.(LIU Hao, born in 1988, Ph. D. candidate. His research interests include machine learning.JIANG Jiangguo, born in 1955, Ph.D., professor. His research interests include intelligent video surveillance, image processing, DSP technology and its application. |
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2016, Vol. 29 
