Perceived age estimation under lighting condition change by covariate shift adaptation

Kazuya Ueki, Masashi Sugiyama, Yasuyuki Ihara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - International Conference on Pattern Recognition
Pages3400-3403
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 2010 Aug 232010 Aug 26

Other

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

Keywords

  • Age estimation
  • Covariate shift adaptation
  • Face recognition
  • Importance-weighted regularized least-squares
  • Kullback-Leibler importance estimation procedure
  • Lighting condition change

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Ueki, K., Sugiyama, M., & Ihara, Y. (2010). Perceived age estimation under lighting condition change by covariate shift adaptation. In Proceedings - International Conference on Pattern Recognition (pp. 3400-3403). [5597530] https://doi.org/10.1109/ICPR.2010.830