Automatic affect analysis: From children to adults

Abstract

This article presents novel and robust framework for automatic recognition of facial expressions for children. The proposed framework also achieved results better than state of the art methods for stimuli containing adult faces. The proposed framework extract features only from perceptual salient facial regions as it gets its inspiration from human visual system. In this study we are proposing novel shape descriptor, facial landmark points triangles ratio (LPTR). The framework was first tested on the “Dartmouth database of children’s faces” which contains photographs of children between 6 and 16 years of age and achieved promising results. Later we tested proposed framework on Cohn-Kanade (CK+) posed facial expression database (adult faces) and obtained results that exceeds state of the art.