Facial Expression Recognition from Video Using Eigen Values

Manish Trivedi, Ruchi Chaurasia, Manoj Tolani

Abstract: facial expressions recognition is now a main area of interest within various fields such as computer science, medicine, and psychology. Facial expressions commit authorized information about emotions of any person. Understanding facial expressions accurately is one of the difficult tasks for interpersonal relationships. Now a days automatic detection of emotions is very popular. We have to build such a efficient approach for human emotion recognition. To improve the human-computer interaction (HCI) to be as good as human-human interaction, building an efficient approach for human emotion recognition is required. These emotions could be blended from several modalities such as facial expression, hand gesture, acoustic data, and biophysiological data. This paper proposes an approach to solve this limitation using salient distance features, which are obtained by extracting patch-based Eigen value, selecting the salient patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), tracking of face and detect the expressions.

Keywords: Facial expression analysis, feature evaluation and selection, computer vision, neural network, Eigen values Eigen faces, Eigen faces, Eigen Vectors, Principal Component Analysis PCA, Linear Discriminant Analysis LDA