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

Overview & Synopsis

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 robust-ness 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.