基于独立成分分析和信息融合的步态识别<sup>*</sup>

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Abstract A gait recognition method is proposed based on independent component analysis/support vector machine (ICA/SVM) and information fusion from multiple views. Human silhouette extraction is obtained by background subtraction and shadow elimination. Wavelet descriptor is applied to describe these silhouettes. Then, independent component analysis is employed to compress and extract their features, and gait classification is performed by support vector machine. The gait features from multiple views are fused, and recognition is finished. The method is evaluated on the National Laboratory of Pattern Recognition (NLPR) and Xi’an University of Technology (XAUT) gait database and the correct recognition rate is relatively high. The experimental results show that the proposed method has good recognition performance.

Key words： Gait Recognition Independent Component Analysis (ICA) Support Vector Machine (SVM) Information Fusion Wavelet Descriptor

Received: 10 April 2006

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	LU JiWen
	ZHANG ErHu
	XUE YanXue

Cite this article:

LU JiWen,ZHANG ErHu,XUE YanXue. Gait Recognition Based on Independent Component Analysis and Information Fusion[J]. , 2007, 20(3): 365-370.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2007/V20/I3/365

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