Facial age estimation based on label-sensitive learning and age-oriented regression
Resource
Pattern Recognition, 46(3), 628-641
Journal
Pattern Recognition
Pages
628-641
Date Issued
2012
Date
2012
Author(s)
Abstract
This paper provides a new age estimation approach, which distinguishes itself with the following three contributions. First, we combine distance metric learning and dimensionality reduction to better explore the connections between facial features and age labels. Second, to exploit the intrinsic ordinal relationship among human ages and overcome the potential data imbalance problem, a label-sensitive concept and several imbalance treatments are introduced in the system training phase. Finally, an age-oriented local regression is presented to capture the complicated facial aging process for age determination. The simulation results show that our approach achieves the lowest estimation error against existing methods. © 2012 Elsevier Ltd.
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Type
journal article
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