Fully Automated Facial Expression Recognition Using 3D Morphable Model and Mesh-Local Binary Pattern

摘要

With recent advances in artificial intelligence and pattern recognition, automatic facial expression recognition draws a great deal of interest. In this area, most of works involved 2D imagery. However, they present some challenges related to pose, illumination variation and self-occlusion. To deal with these problems, we propose to reconstruct the face in 3D space, from only one 2D image, using the 3D Morphable Model (3DMM). Thus, thanks to its robustness against pose and illumination variations, 3DMM offers high-resolution model and fast fitting functionality. Then, given the reconstructed 3D face, we extract a set of features, which are effective to describe shape changes and expression-related facial appearance, using Mesh-Local Binary Pattern (mesh-LBP). Obtained results proved the effectiveness of combining 3DMM and mesh-LBP for automatic facial expression recognition from 2D single image. In fact, to evaluate the proposed method against state-of-the-art methods, a comparative study shows that the method outperforms existing ones.