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.
作者简介: 齐美彬,男,1969年生,博士,教授,主要研究方向为智能视频监控、DSP技术及其应用.E-mail:qimeibin@163.com.檀胜顺,男,1990年生,硕士研究生,主要研究方向为目标检索.(TAN Shengshun, born in 1990, master student. His research interests include object retrieval.)刘 皓,男,1988年生,博士研究生,主要研究方向为机器学习.蒋建国,男,1955年生,博士,教授,主要研究方向为智能视频监控、图像处理、DSP技术及其应用.
引用本文:
齐美彬，王运侠，檀胜顺，刘皓，蒋建国. 正则化独立测度矩阵的行人再识别*[J]. 模式识别与人工智能, 2016, 29(6): 511-518.
QI Meibin, WANG Yunxia, TAN Shengshun, LIU Hao, JIANG Jianguo. Person Re-identification Based on Regularization of Independent Measure Matrix. , 2016, 29(6): 511-518.
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