Smile veracity recognition using 3D texture features for image sequence processing

Abstract

Emotions are one of the most important cues of non-verbal communication, therefore are easily recognized by people. However, correct identification of intentions causes many problems, because telling apart the true emotion expression from the fake one is difficult. Therefore, there is a wide search nowadays for automatic techniques, which use computers to analyze behavior of people and learn the differences between spontaneous and posed emotional gestures. In this research we concentrate on the analysis of facial expressions in order to recognize between Duchenne (real) and fake smiles. Our approach treats the input movie as a dynamic texture and exploits LBP-TOP technique for its description. Additionally, the average facial image is removed from consideration as it is assumed, that only tiny changes differ the smile characters. The results obtained on UVA-NEMO dataset proved that it is possible to classify accurately between the spontaneous and posed smiles. Moreover, the influence of facial parts as well as changes due to a phase of smile are investigated.