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.
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Zhai, CM., Qing, Y., Ji-xiang, D. (2010). Age Estimation of Facial Images Based on an Improved Non-negative Matrix Factorization Algorithms. In: Huang, DS., Zhang, X., Reyes García, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_83
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DOI: https://doi.org/10.1007/978-3-642-14932-0_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14931-3
Online ISBN: 978-3-642-14932-0
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