Feature extraction through Binary Pattern of Phase Congruency for facial expression recognition

Abstract

Although facial expression plays an important role in human interaction, automated facial expression analysis is still a challenging task. This paper presents a novel facial descriptor based on Phase Congruency (PC) and Local Binary Pattern (LBP) for facial expression recognition. The proposed descriptor, named Binary Pattern of Phase Congruency (BPPC), is an oriented and multi-scale local descriptor that is able to encode various patterns of face images. It is constructed by applying LBP on the oriented PC images. We evaluated the proposed method using the Cohn-Kanade (CK <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+</sup> ) database. In our experiment, we achieved an overall detection rate of 93.83% for the six basic emotions. This shows the effectiveness of the proposed method.