Gender Classification Method Based on Gait Energy Motion Derived from Silhouette Through Wavelet Analysis of Human Gait Moving Pictures
Автор: Kohei Arai, Rosa Andrie Asmara
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 3 Vol. 6, 2014 года.
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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.
Gender Classification, Human Gait, Gait Energy Motion, Wavelet Analysis
Короткий адрес: https://sciup.org/15012054
IDR: 15012054
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