Emotion Recognition from the Lip-Contour of a Subject Using Artificial Bee Colony Optimization Algorithm

Abstract

AbstractThis paper provides an alternative approach to emotion recognition from the outer lip-contour of the subjects. Subjects exhibit their emotions through their facial expressions, and the lip region is segmented from their facial images. A lip-contour model has been developed to represent the boundary of the lip, and the parameters of the model are adapted using artificial bee colony (ABC) optimization algorithm to match it with the boundary contour of the lip. An SVM classifier is then employed to classify the emotion of the subject from the parameter set of the subjects’ lip-contour. The experiment was performed on 50 subjects, and the average case accuracy in emotion classification is found to be 86%.Keywordslip contourartificial bee colony optimization algorithmsupport vector machine