A Gait Feature Extraction Algorithm Based on Fusion of Spatial and Frequency Feature

Xiao Ke Zhu; Xiao Pan Chen; Fan Zhang

doi:10.4028/www.scientific.net/AMM.291-294.2492

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 291-294A Gait Feature Extraction Algorithm Based on...

A Gait Feature Extraction Algorithm Based on Fusion of Spatial and Frequency Feature

Abstract:

In order to enhance the accuracy of gait recognition, a new gait feature extraction algorithm is proposed. Firstly, the gait images are preprocessed to extract moving objects, including background modeling, moving object extracting and morphological processing. Secondly, an equidistant slicing curve model based on system of polar coordinate is designed to slice the moving object, and the slicing vector is used to describe the spatial feature; Thirdly, the slicing vector is converted into frequency signal by Fourier transform to extract the frequency feature. Finally, the above two features are fused and used for the classification. The experimental results show that proposed algorithm provides higher correct classification rate than the algorithms using single feature, and meets the requirements of the real-time.

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Periodical:

Applied Mechanics and Materials (Volumes 291-294)

Pages:

2492-2495

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.291-294.2492

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Online since:

February 2013

Authors:

Xiao Ke Zhu, Xiao Pan Chen, Fan Zhang

Keywords:

Equidistant Slicing Vector, Feature Fusion, Fourier Transform, Gait Feature

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