3D facial expression recognition using distance features and LBP features based on automatically detected keypoints

摘要

The 3D facial surface demonstrates rich information about human beings' expressions. However, methods to recognize humans' facial expression are mainly still focusing on 2D images, which is not robust to pose and lighting conditions. In this paper, the problem of the person-independent facial expression recognition is addressed on basis of the line segments connected by specific 3D automatically detected facial keypoints and LBP features of depth images around the automatically detected facial keypoints. Using a Support Vector Machine classifier, the recognition rate reaches up to 92.1% on the BU-3DFE database. Comparative analysis shows that our method outperforms the competitor approaches using similar experimental settings, which proves the effectiveness of our method for 3D facial expression recognition.