Age Estimation Based on AAM and 2D-DCT Features of Facial Images
نویسندگان
چکیده
This paper proposes a novel age estimation method Global and Local feAture based Age estiMation (GLAAM) relying on global and local features of facial images. Global features are obtained with Active Appearance Models (AAM). Local features are extracted with regional 2D-DCT (2dimensional Discrete Cosine Transform) of normalized facial images. GLAAM consists of the following modules: face normalization, global feature extraction with AAM, local feature extraction with 2D-DCT, dimensionality reduction by means of Principal Component Analysis (PCA) and age estimation with multiple linear regression. Experiments have shown that GLAAM outperforms many methods previously applied to the FG-NET database. Keywords—2D-DCT; AAM; Age estimation; PCA; Regression
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تاریخ انتشار 2015