Improved 3D face reconstruction from stereo images

This paper presents an approach for stereo-based 3D face reconstruction. Our approach is based on depth estimation of the face by using the stereo image pair, requiring neither expensive devices nor generic face models. In order to improve the depth estimation, our approach incorporates face properties to enhance the 3D face reconstruction. The approach starts with a sparse disparity map with 68 facial landmarks detected by dlib toolkit. Considering the face symmetry and smoothness, we complete the dense disparity estimation with the guidance of the sparse disparity map. Post-processing is implemented including outliers removal and surface mesh. Experimental results provided show that the algorithm is promising.