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Journal of Electronic Imaging

Gait recognition based on Gabor wavelets and modified gait energy image for human identification
Author(s): Deng-Yuan Huang; Ta-Wei Lin; Wu-Chih Hu; Chih-Hsiang Cheng
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Paper Abstract

This paper proposes a method for recognizing human identity using gait features based on Gabor wavelets and modified gait energy images (GEIs). Identity recognition by gait generally involves gait representation, extraction, and classification. In this work, a modified GEI convolved with an ensemble of Gabor wavelets is proposed as a gait feature. Principal component analysis is then used to project the Gabor-wavelet-based gait features into a lower-dimension feature space for subsequent classification. Finally, support vector machine classifiers based on a radial basis function kernel are trained and utilized to recognize human identity. The major contributions of this paper are as follows: (1) the consideration of the shadow effect to yield a more complete segmentation of gait silhouettes; (2) the utilization of motion estimation to track people when walkers overlap; and (3) the derivation of modified GEIs to extract more useful gait information. Extensive performance evaluation shows a great improvement of recognition accuracy due to the use of shadow removal, motion estimation, and gait representation using the modified GEIs and Gabor wavelets.

Paper Details

Date Published: 20 December 2013
PDF: 11 pages
J. Electron. Imaging. 22(4) 043039 doi: 10.1117/1.JEI.22.4.043039
Published in: Journal of Electronic Imaging Volume 22, Issue 4
Show Author Affiliations
Deng-Yuan Huang, Da-Yeh Univ. (Taiwan)
Ta-Wei Lin, Da Yeh Univ. (Taiwan)
Wu-Chih Hu, National Penghu Univ. of Science and Technology (Taiwan)
Chih-Hsiang Cheng, Da Yeh Univ. (Taiwan)

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