Learning Encoded Facial Curvature Information for 3D Facial Emotion Recognition

摘要

In current 3D facial expression recognition system, feature extraction has always been a critical point. We focus on encoding feature by using curvature information. 3D facial expression images are described by means of four images which gray level are the value of curvature-based descriptors (principal curvatures k1, k2, mean curvature, shape index) and then encoded by LBP. SVM classifier is employed for classification. Then experimental result illustrates that the proposed feature classified by SVM is effective.