A Correlation Based Approach to Human Gait Recognition

T. Amin, D. Hatzinakos
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引用次数: 3

Abstract

This paper presents a new gait signature for human gait recognition which is based on the correlation analysis of the leg motion. The motion of two legs during the human walking process is one of the most important gait determinants. This cyclic motion of the two legs is extracted by applying 2-D masks on the relevant areas of the binary images. Experimental results indicate that 2nd. order and 1-D diagonal slice of 3rd. order autocorrelations of these area signals possesses significant discrimination power to build an effective gait recognition system.
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一种基于相关性的人体步态识别方法
提出了一种基于腿部运动相关性分析的步态特征识别方法。在人类行走过程中,两条腿的运动是最重要的步态决定因素之一。这种两条腿的循环运动是通过在二值图像的相关区域上应用二维掩模来提取的。实验结果表明:2。阶和3的一维对角线切片。这些区域信号的阶自相关性具有显著的判别能力,可以构建有效的步态识别系统。
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