Paper Info
Title
Gait recognition based on Gabor wavelets and modified gait energy image for human identification
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. (C) 2013 SPIE and IS&T
Year
DOI
Venue
2013
10.1117/1.JEI.22.4.043039
JOURNAL OF ELECTRONIC IMAGING
Keywords
Field
DocType
gait recognition,background subtraction,gait energy image,Gabor wavelets,support vector machine,motion estimation
Computer vision,Feature vector,Pattern recognition,Radial basis function kernel,Gait,Computer science,Gabor wavelet,Segmentation,Support vector machine,Artificial intelligence,Motion estimation,Wavelet
Journal
Volume
Issue
ISSN
22
4
1017-9909
Citations 
PageRank 
References 
3
0.40
0
Authors
4
Name
Order
Citations
PageRank
Deng-Yuan Huang1382.35
Ta-Wei Lin2544.58
Wu-Chih Hu324427.01
Chih-Hsiang Cheng430.40