Facial age estimation based on label-sensitive learning and age-oriented regression

PATTERN RECOGNITION

卷:46

Article

Chao, Wei-Lun¹  Liu, Jun-Zuo¹  Ding, Jian-Jiun¹ 

[1] Natl Taiwan Univ, Grad Inst Commun Engn, Taipei 10617, Taiwan

关键词: Machine learning;    Pattern recognition;    Manifold learning;    Dimensionality reduction;    Distance metric learning;    Local regression;    Age estimation;   

DOI  :  10.1016/j.patcog.2012.09.011

来源: Elsevier

【 摘 要 】

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. (C) 2012 Elsevier Ltd. All rights reserved.

【 授权许可】

Free