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ICPR
2010
IEEE

Perceived Age Estimation under Lighting Condition Change by Covariate Shift Adaptation

11 years 5 months ago
Perceived Age Estimation under Lighting Condition Change by Covariate Shift Adaptation
—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. Keywords-face recognition; age estimation; covariate shift adaptation; lighting condition change; Kullback-Leibler importance estimation procedure; importance-weighted regularized least-squares
Kazuya Ueki, Masashi Sugiyama, Yasuyuki Ihara
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2010
Where ICPR
Authors Kazuya Ueki, Masashi Sugiyama, Yasuyuki Ihara
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