Perceived age estimation under lighting condition change by covariate shift adaptation

Kazuya Ueki*, Masashi Sugiyama, Yasuyuki Ihara

*この研究の対応する著者

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Over the recent years, a great deal of effort has been made to age estimation from face images. It has been reported that age can be accurately estimated under controlled environment such as frontal faces, no expression, and static lighting conditions. However, it is not straightforward to achieve the same accuracy level in real-world environment because of considerable variations in camera settings, facial poses, and illumination conditions. In this paper, we apply a recently-proposed machine learning technique called covariate shift adaptation to alleviating lighting condition change between laboratory and practical environment. Through real-world age estimation experiments, we demonstrate the usefulness of our proposed method.

本文言語English
ホスト出版物のタイトルProceedings - International Conference on Pattern Recognition
ページ3400-3403
ページ数4
DOI
出版ステータスPublished - 2010
外部発表はい
イベント2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
継続期間: 2010 8月 232010 8月 26

Other

Other2010 20th International Conference on Pattern Recognition, ICPR 2010
国/地域Turkey
CityIstanbul
Period10/8/2310/8/26

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識

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