Clustering Based Reference Normal Pose for Improved Expression Recognition

Abstract

In this paper the theme of automatic face expression identification is approached. We propose a robust method to identify the neutral face of a person while showing various expressions. The method consists in separating various images of faces based on expressions with a clustering method and retrieving the neutral face as being in the image closest to the centroid of the dominant cluster. The so found neutral face is used in conjunction with an expression detection method. We tested the method on the Extended Cohn-Kanade database where we identify correctly the neutral face with 100% accuracy and on the UNBC McMaster Pain Shoulder database where the use of the neutral pose leads to an increase of 10% in accuracy thus entering in the range of state of the art in pain detection.