A depth video-based facial expression recognition system using radon transform, generalized discriminant analysis, and hidden Markov model

Abstract

In this paper, a depth camera-based novel method is proposed to recognize several facial expressions from depth video. At first, Radon Transformation (RT) is done to extract features from the time-sequential depth faces that are further improved by Generalized Discriminant Analysis (GDA) to generate more robust features and then, Hidden Markov Models (HMMs) are applied to train and recognize different facial expressions successfully. Performance of the proposed facial expression recognition shows the superiority over conventional RGB camera-based approaches.