Abstract
The face aging process is subject to multiple influences. This may probably involve several inherited and various environmental and biological factors like the differences observed between males and females. In fact, male and female facial skin differs as far as the type, the consistency and the sensitivity to external factors is concerned. In this paper, we proposed a new age classification method that consists of classifying human faces into various age groups by exploring the correlation between age and gender information. Moreover, we suggested a two-level age classification to reduce confusion between age groups. Our experiments were conducted on the Adience benchmark and the FG-Net dataset for the age classification and on the Groups and FERET datasets for the gender estimation. The experimental results reveal the good performance of our method while identifying the age groups in challenging contexts.
Published Version
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