A Method for Human Emotion Recognition System

This paper studied computationally efficient algorithm for facial feature selection based on template matching method which further leads to identification of smiling face or neutral face. At first, minimal pre-processing including gray scale conversion is done on the image. After that, matching between original image and template image is done using normalized cross-correlation technique. Each matching area is bounded by box to identify that region of interest. Then the mid points between the eye regions are found and the distance between the mid points and the corners of the mouth region is calculated. On the basis of the distances between these features, emotions are recognized. After detecting neutral or smiling face, different types of facial expressions are classified using linear support vector machine used as multiclass classifier.