Age estimation of facial images based on a super-resolution reconstruction algorithm

Authors:
Jie Kou;Ji-Xiang Du;Chuan-Min Zhai
Affiliations:
Department of Computer Science and Technology, Huaqiao University, Xiamen, China;Department of Computer Science and Technology, Huaqiao University, Xiamen, China;Department of Computer Science and Technology, Huaqiao University, Xiamen, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

Automatic age estimation based on facial images is important but challenging in face recognition research. A Super-Resolution Reconstruction algorithm was proposed to implement the age estimation of facial images, which cut the facial image into small pieces. Then after building high resolution images by using Super-Resolution Reconstruction algorithm, the RBF neural networks was used to train and test these high resolution images. At last, the classifier ensemble with genetic algorithm was used to estimating age information. Finally, experimental results demonstrate that it is an effective method.