Ensemble of global and local features for face age estimation

Authors:
Wankou Yang;Cuixian Chen;Karl Ricanek;Changyin Sun
Affiliations:
Face Aging Group, Dept. Of Computer Science, UNCW and School of Automation, Southeast University, Nanjing, China;Face Aging Group, Dept. Of Computer Science, UNCW;Face Aging Group, Dept. Of Computer Science, UNCW;School of Automation, Southeast University, Nanjing, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Year:
2011

Citing 7
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Abstract

Automatic face age estimation is a challenging task due to its complexity owing to genetic difference, behavior and environmental factors, and also the dynamics of facial aging between different individuals. In this paper, we propose a feature fusion method to estimate the face age via SVR, which ensembles global feature from Active Appearance Model (AAM) and the local feature from Gabor wavelet transformation. Our experimental results on UIUC-PAL database show that our proposed method works well.