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赵永伟, 张二虎, 鲁继文, 胡峻林(西安理工大学信息科学系,西安 710048)

摘 要
Gait Recognition Via Multiple Features and Views Information Fusion

ZHAO Yongwei, ZHANG Erhu, LU Jiwen, HU Junlin(Department of Information Science, Xi’an University of Technology, Xi’an 710048)

A new gait recognition method based on information fusion of multiple kinds of features and views is proposed in this paper. Through the background subtraction and shadow elimination, human motion silhouettes are obtained and gait features are extracted using pseudo-Zernike moment, wavelet descriptor and Procrustes shape analysis. The gait recognition is accomplished through information fusion of multiple kinds of features and views on feature level and decision level. The method is evaluated on the CASIA gait database and received comparative high correct recognition rate. The experimental results show that our approach has efficient recognition performance.