Magnitude and phase spectra of foot motion for gait recognition

Authors:
Agus Santoso Lie;Shuichi Enokida;Tomohito Wada;Toshiaki Ejima
Affiliations:
Department of Artificial Intelligence, Kyushu Institute of Technology, Iizuka City, Fukuoka Pref., Japan;Department of Artificial Intelligence, Kyushu Institute of Technology, Iizuka City, Fukuoka Pref., Japan;National Institute of Fitness and Sports in Kanoya, Kanoya City, Kagoshima Pref., Japan;Department of Artificial Intelligence, Kyushu Institute of Technology, Iizuka City, Fukuoka Pref., Japan
Venue:
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Year:
2005

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Abstract

Magnitude and phase spectra of horizontal and vertical movement of ankles in a normal walk are effective and efficient signatures in gait recognition. An approach to use these spectra as phase-weighted magnitude spectra is also widely known. In this paper, we propose an integration of magnitude and phase spectra for gait recognition using AdaBoost classifier. At each round, a weak classifier evaluates each magnitude and phase spectra of a motion signal as dependent sub-features, then classification results of each sub-feature are normalized and summed for the final hypothesis output. Experimental results in same-day and cross-month tests with nine subjects show that using both magnitude and phase spectra improves the recognition results.