A method of gender classification by integrating facial, hairstyle, and clothing images

Kazuya Ueki*, Hiromitsu Komatsu, Satoshi Imaizumi, Kenichi Kaneko, Satoshi Imaizumi, Nobuhiro Sekine, Jiro Katto, Tetsunori Kobayashi

*この研究の対応する著者

研究成果: Conference contribution

24 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
編集者J. Kittler, M. Petrou, M. Nixon
ページ446-449
ページ数4
DOI
出版ステータスPublished - 2004 12 20
イベントProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
継続期間: 2004 8 232004 8 26

出版物シリーズ

名前Proceedings - International Conference on Pattern Recognition
4
ISSN(印刷版)1051-4651

Conference

ConferenceProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
国/地域United Kingdom
CityCambridge
Period04/8/2304/8/26

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

引用スタイル