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We study the problem of cross-population age estimation. Human aging is determined by the genes and influenced by many factors. Different populations, e.g., males and females, Caucasian and Asian, may age differently. Previous research has discovered the aging difference among different populations, and reported large errors in age estimation when crossing gender and/or ethnicity. In this paper we...
Big Data analysis is an emerging topic in computer vision and pattern recognition. As one example problem of big data, we study semantic age labels and facial aging pattern analysis on a large database. In aging analysis, one of the great challenges is the lack of a large number of face images with ground truth age labels. Unlike many other example-based recognition problems where human annotations...
Human age, as an important personal trait, can be directly inferred by distinct patterns emerging from the facial appearance. Derived from rapid advances in computer graphics and machine vision, computer-based age synthesis and estimation via faces have become particularly prevalent topics recently because of their explosively emerging real-world applications, such as forensic art, electronic customer...
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