3D face modeling based on SFM algorithm

This paper proposes a whole scheme to construct textured 3D face models from two views with a few user interactions. As the human face contains many low texture and homogeneous areas, some algorithms such as corner matching are unstable and may fail sometimes. This paper uses the face definition parameters and the symmetry of human face as prior knowledge to find reliable correspondences between two pictures, while most SFM algorithms use the generic model as a modulator in the post-processing steps. According to the correspondences, a multistage SFM approach is used to reconstruct the structure. Then the authors use the RBFCS algorithm to interpolate more 3D points according to the scattered feature points. Multistage image mosaic technique is used to get the texture. A user with an ordinary camera can use the algorithm to generate his realistic face model in a personal computer.