Age estimation of facial images based on an improved non-negative matrix factorization algorithms

Authors:
Chuan-Min Zhai;Yu Qing;Du Ji-Xiang
Affiliations:
Department of Computer Science and Technology, Huaqiao University, Quanzhou;Department of Computer Science and Technology, Huaqiao University, Quanzhou;Department of Computer Science and Technology, Huaqiao University, Quanzhou and Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui
Venue:
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Year:
2010

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Abstract

Based on facial images, automatic age estimation has been recently a new hotspot, which is also an important but challenging study in the field of face recognition. An improved NMF (Non-negative Matrix Factorization) algorithm was used to implement the age estimation of facial images, which can keeps down the base images that have the best discriminate ability through a selection method to form a new subspace. Then, after project the whole training sets images to the obtained subspace, the RBF (Radial Basis Function) neural networks has been used as predictor to perform automatic age estimation. Finally, experimental results demonstrate that it is an effective method.