A Frequency Domain Analysis Based Gait Feature Representation

Author

Mu, Hong-bo ; Yu, Xin-Cen ; Wang, Chong-Jun

Author_Institution

Dept. of Comput. Sci. & Technol., Nanjing Univ., Nanjing, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

6

Abstract

A method for representing gait feature based on frequency domain analysis is proposed. For a gait represented by a sequence of binarized silhouettes, its frequency domain feature is extracted following period detection, contour extraction and unwrapping, distance normalization, 2D Fourier transform, feature frequencies computation and some other procedures. Nearest neighbor classifier is used to test its usefulness for gait recognition purpose, and experiment result, compared with previously conducted research, shows that the proposed gait feature representation is soundly effective.

Keywords

Fourier transforms; feature extraction; frequency-domain analysis; gait analysis; image recognition; image representation; 2D Fourier transform; binarized silhouettes; contour extraction; distance normalization; feature extraction; frequency domain analysis; gait feature representation; gait recognition; nearest neighbor classifier; period detection; Biometrics; Face recognition; Fourier transforms; Frequency domain analysis; Humans; Nearest neighbor searches; Principal component analysis; Shape; Signal processing; Target recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5364468

Filename

5364468