Abstract
As we all know, face age estimation task is not only challenging for computer, but even hard for human in some cases, however, coarse age classification such as classifying human face as baby, child, adult or elder people is much easier for human. In this paper, we try to dig out the potential age classification power of computer on faces from consumer images which are taken under various conditions. Gabor feature is extracted and used in LDA classifiers. In order to solve the intrinsic age ambiguity problem, a fuzzy version LDA is introduced through defining age membership functions. Systematic comparative experiment results show that the proposed method with Gabor feature and fuzzy LDA can achieve better age classification precision in consumer images.
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Gao, F., Ai, H. (2009). Face Age Classification on Consumer Images with Gabor Feature and Fuzzy LDA Method. In: Tistarelli, M., Nixon, M.S. (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_14
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DOI: https://doi.org/10.1007/978-3-642-01793-3_14
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