ABSTRACT
Analysis of human emotion from the sequence of face images is a vital issue for a person to recognize the changes in emotional behavior. In this work, we propose an effective method for recognition of temporal dynamic variations in human emotion from facial video frames that used a triangulation mechanism to generate triangles on the face. In our approach, angular information extracted from every triangle generated by landmark points is taken into the account as geometric features that help us to distinguish human emotion into different basic facial expressions like anger, 74disgust, fear, happiness, sadness, and surprise. Besides, we considered important regions on the face to get relevant geometric features that discriminate an image sequence from others. For verification of the performance of our proposed method, we experimented with our emotion recognition system on different benchmark image sequence databases like Extended Cohn-Kanade(CK+), MMI and MUG. A comparison in experimental results obtained from different databases encompasses the efficiency of the proposed method with a promising recognition rate.
