Application of General Type-2 Fuzzy Set in Emotion Recognition from Facial Expression

This paper proposes a new technique for emotion recognition of an unknown subject using General Type-2 Fuzzy sets (GT2FS). The proposed technique includes two steps- first, a type-2 fuzzy face-space is created with the background knowledge of facial features of different subjects containing different emotions. Second, the emotion of an unknown facial expression is determined based on the consensus of the measured facial features with the fuzzy face-space. The GT2FS has been used here to model the fuzzy face space. The general type-2 fuzzy involves both primary and secondary membership distributions which have been obtained here by formulating and solving an optimization problem. The optimization problem here attempts to minimize the difference between two decoded signals: the first one being the type-I defuzzification of the average primary membership distributions obtained from n-subjects, while the second one refers to the type-2 defuzzified signal for a given primary distribution with secondary memberships as unknown. The uncertainty management policy adopted using general type-2 fuzzy set has resulted in a classification accuracy of 96.67%.