Gait recognition using fractal scale

Authors:
Guoying Zhao;Li Cui;Hua Li
Affiliations:
Univ. of Oulu, Mach. Vis. Grp., Infotech Oulu and Dept. of Elec. and Info. Eng., Finland and Inst. of Comp. Tech. (ICT), Ch. Acad. Sci. (CAS), Key Lab. of Intell. Info. Proc. and (CAS), Natnl. Res ...;Beijing Normal University, School of Mathematics Science, P.O. Box 4500, 100875, Beijing, China;Inst. of Comp. Technol., Ch. Acad. Sci., Key Lab. of Intell. Info. Proc., Beijing and Ch. Acad. Sci., Natnl. Res. Ctr. for Intell. Comp. Sys., Inst. of Comp. Technol., Beijing, 100080, China
Venue:
Pattern Analysis & Applications
Year:
2007

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Abstract

Gait is an identifying biometric feature. Video-based gait recognition has now become a new challenging topic in computer vision. In this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. Fractal scale, which is based on wavelet analysis, represents the self-similarity of signals, and improves the flexibility of wavelet moments. It is translation, scale and rotation invariant, and has anti-noise and occlusion handling performance. Moreover, by introducing the Mallat algorithm of wavelet, it reduces the computation complexity. Experiments on three databases show that fractal scale has simple computation and is an efficient descriptor for gait recognition.