Dense Optical Flow Based Emotion Recognition Classifier

In recent years, enabling computer systems to recognize facial expressions and infer emotions from them in real time has become very important since such information can be used in emerging applications such as video games, educational software, computer-based tutoring for special need children for better human computer interactions. However, real time emotion recognition using video streams face challenges due to the varying illuminations. In this paper, we present a real time emotion recognition scheme using dense optical flow based approach and SVM classifier. Via extensive analysis using newly collected datasets of 370 videos, we demonstrate that our approach demonstrates high accuracy in recognizing 4 basic emotions: happy, angry, surprise and sad.