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Lighting Condition Adaptation for Perceived Age Estimation
Kazuya UEKI Masashi SUGIYAMA Yasuyuki IHARA
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2011/02/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
face recognition, age estimation, covariate shift adaptation, lighting condition change, Kullback-Leibler importance estimation procedure, importance-weighted regularized least-squares,
Full Text: PDF(158.3KB)
Over the recent years, a great deal of effort has been made to estimate age 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 a real-world environment due to 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.