Age estimation using hybrid features of facial images

Abstract

This paper presents a novel age estimation method using hybrid features, which are the combination of global and local features of facial images. Global and local features are extracted using Active Appearance Models and Discrete Cosine Transform, respectively. Then these features are fused in the feature level, and the age is estimated using multiple linear regression. Experiments on FG-NET database have shown that, the hybrid features improves the age estimation performance.