Emotion Recognition Based on Interval Type-2 Fuzzy Logic from Facial Expression

Authors : Mahmut DİRİK, Oscar CASTILLO, A. Fatih KOCAMAZ

Pages : 1-17

View : 20 | Download : 9

Publication Date : 2020-06-15

Article Type : Research Paper

Abstract :Automatic recognition of facial emotion plays an effective and important role in Human–Computer Interaction insert ignore into journalissuearticles values(HCI);. There are various emotion recognition approaches have been proposed in the literature. The analytic face model consisted of a 26-dimensional geometric feature vector. These properties are used effectively to identify facial changes resulting from different expressions. The variation and uncertainties of these features make the emotion recognition problem more complicated. For decreasing these complications, we propose a distance-based clustering and uncertainty measures of the base new method for Emotion Recognition from Facial Expression using automatically selects 19 diagnostics of Action Units insert ignore into journalissuearticles values(AUs); in a 2D facial image using Type-2 Fuzzy inference system. The proposed system includes an automated generation scheme of the geometric facial feature vector. The proposed system has classified six facial expressions using the MUG Facial Expression database. The experimental results show that the proposed model is very efficient in uncertainty management policy and recognizes six basic emotions with an average precision rate of 86.175%.
Keywords : Action Unit, Emotion Recognition, Facial Expression Recognition, HumanComputer Interaction, Interval Type 2 Fuzzy System