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| A Multi-layer Windows Method of Moments for Gait Recognition |
| Chen Shi①; Ma Tian-jun②; Huang Wan-hong①; Gao You-xing② |
| ①School of Design, Zhejiang Wanli University, Ningbo 315100, China;②School of Computer Science and Technology, Xidian University, Xi’an 710071, China |
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Abstract A feature representation method based on multi-layer local moment invariants for gait analysis and recognition applications is developed. The method includes following steps: first, silhouette extraction is performed for each image sequence. Secondly, the gait cycle is detected by a histogram-based approach. Thirdly, a scalarvalued CGHI(Colored Gait History Images) is proposed to describe how human walking is evolved. To improve the recognition rate, the CGHI is decomposed into a sequnce of muti-layer rectangle windows. The moment invariants from the window are used as the gait features and finally used to recognize gait. The correct classification rate of 87.2% is achieved on Soton database, which show that the method outperforms the exist methods.
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Received: 08 August 2007
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2009, Vol. 31 
