提出了一种基于多特征和多视角信息融合的步态识别方法。应用背景差分和阴影消除获得人体步态轮廓，对人体轮廓使用伪Zernike矩、小波描述子和Procrustes形状分析法进行了特征提取。通过多特征和多视角步态信息融合，完成了基于人体步态特征的身份识别。该方法在CASIA步态数据库上进行了实验，取得了较高的正确识别率，实验结果表明本文所提出的识别方法具有较高的识别性能。

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.