Modification of Happiness Expression in Face Images

Abstract

This article describes how facial expression detection and adjustment in complex psychological aspects of vision is central to a number of visual and cognitive computing applications. This article presents an algorithm for automatically estimating happiness expression of face images whose demographic aspects like race, gender and eye direction are changeable. The method is also broadening for alteration of level of happiness expression for face images. A schema of the weighted modification is proposed for enhancement of happiness expression. The authors employ a robust face representation which combines the color patch similarity and the self-resemblance of image patches. A large set of face images with appearance of the properties is learned in a statistical model for interpreting the facial expression of happiness. The authors will show the experiments of such a model using face features for learning by SVM and analyze the performance.