Abstract
AbstractAutomatic age estimation from facial images is emerging as an important research area in recent years due to its promising potential for some computer vision applications. In this paper we propose a novel approach combine the global and local facial features in parallel manner to implement the age estimation. Then after extracting global and local features, these features are integrated for fine classification. In the proposed method, global and local features are extracted by Discrete Fourier Transform (DFT) and Principal Component Analysis (PCA) respectively. We have conducted experiments on a large scale age databases (FGNET). The experimental results are very promising in showing that it is an effective methodKeywordsage estimationglobal featurelocal featureclassifier integration
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