Classifying driver facial emotions

Abstract

This paper describes the emotion recognition to determine the driver’s conditions. The emotion recognition could be envisioned to sense the driver emotions automatically through a camera. Therefore, facial images were analyzed to extract the features to characterize the variations between facial emotions images. The features extraction techniques apply was Principal Component Analysis (PCA), this algorithm finds the principle components of the covariance matrix of a set of face images. Then, the eigenvalues component will be used as an input to the KNearest Neighbor (KNN) classifier. The facial expression recognition used to investigate the emotion and thus carry out an awareness system for drivers to perform an appropriate intervention system.