A Method of Gender Classification by Integrating Facial, Hairstyle, and Clothing Images

Authors:
Kazuya Ueki;Hiromitsu Komatsu;Satoshi Imaizumi;Kenichi Kaneko;Nobuhiro Sekine;Jiro Katto;Tetsunori Kobayashi
Affiliations:
Waseda University, Japan;Waseda University, Japan;Waseda University, Japan;NEC Soft, Ltd., Japan;NEC Soft, Ltd., Japan;Waseda University, Japan;Waseda University, Japan
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Year:
2004

Citing 0
Cited 3

Gender classification by combining clothing, hair and facial component classifiers

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Gender Recognition Based On Combining Facial and Hair Features

Proceedings of International Conference on Advances in Mobile Computing & Multimedia

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Abstract

This paper presents a method of gender classification by integrating facial, hairstyle, and clothing images. Initially, input images are separated into facial, hairstyle and clothing regions, and independently learned PCAs and GMMs based on thousands of sample images are applied to each region. The classification results are then integrated into a single score using some known priors based on the Bayes rule. Experimental results showed that our integration strategy significantly reduced error rate in gender classification compared with the conventional facial only approach.