Face Expression Classification Using Neural Network and PCA algorithm

The purpose of this article is to shed light on the mechanism and the procedures of a program that classifies an input face into any of the six basic facial expressions, which are Anger, Disgust, Fear, Happiness, Sadness and Surprise, in addition to normal face. This program works by apply PCA- principal component analysis algorithm, which is applied of one side of the face, and depends, on contrast to the traditional studies which rely on the whole face, on three components: Eyebrows, Eyes and Mouth. Those out-value are used to determine the facial feature array as an input to the neural network, and the neural network is trained by using the back-propagation algorithm. Note that the faces used in this study belong to people from different ages and races.