Gender Classification Method Based on Gait Energy Motion Derived from Silhouette Through Wavelet Analysis of Human Gait Moving Pictures | Zendy

Kohei Arai | Zendy; Rosa Andrie Asmara | Zendy

Open Access

Gender Classification Method Based on Gait Energy Motion Derived from Silhouette Through Wavelet Analysis of Human Gait Moving Pictures

Author(s) -

Kohei Arai,

Rosa Andrie Asmara

Publication year - 2014

Publication title -

international journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2074-9015

pISSN - 2074-9007

DOI - 10.5815/ijitcs.2014.03.01

Subject(s) - silhouette , computer science , gait , artificial intelligence , computer vision , motion (physics) , wavelet , gait analysis , human motion , motion analysis , pattern recognition (psychology) , physical medicine and rehabilitation , medicine

Gender classification method based on Gait Energy Motion: GEM derived through wavelet analysis of human gait moving pictures is proposed. Through experiments with human gait moving pictures, it is found that the extracted features of wavelet coefficients using silhouettes images are useful for improvement of gender classification accuracy. Also, it is found that the proposed gender classification method shows the best classification performance, 97.63% of correct classification ratio.

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