Expressive 3D face synthesis by multi-space modeling

Parameterization of facial expressions is essential in generating vivid virtual avatars. This paper proposes a novel 3D parameterization method of facial images for expressive face synthesis by multi-space modeling. Given a face photograph, we first build a 3D face model by synthesizing in the facial shape space. The selected key expressions from the facial expression space are then transferred to the newly synthesized facial shape. Finally, with the purpose to produce accurate timing of 3D facial animation, blending coefficients of each frame are estimated in the individual blend coefficientspsila space with regard to motion capture data. By utilizing the advantages of multiple spaces, i.e. facial shape space, facial expression space and individual blend coefficientspsila space, our algorithm provide an effective parameterization solution of facial images. The experiments show that our method can produce promising results of expressive 3D faces of those whose face even only appeared once in the cyberspace.