Learning-based encoding with soft assignment for age estimation under unconstrained imaging conditions

In this paper we propose to adopt a learning-based encoding method for age estimation under unconstrained imaging conditions. A similar approach [Cao et al., 2010] is applied to face recognition in real-life face images. However, the feature vectors are encoded in hard manner i.e. each feature vector is assigned to one code. The face is divided into patches where a code histogram is built for each patch. However, the codebook is learned using sample features from the entire face.