Subtle Facial Animation Transfer from 2D Videos to 3D Faces with Laplacian Deformation

Realistic facial animation transfer from one individual to others has been a persistent challenge. In this paper, we present an effective method that transfers facial animation from 2D videos onto 3D faces in a visually pleasing manner. Our method is based on a Laplacian deformation framework. We represent the facial animation with the displacements of a set of feature points. By the assumption that the feature points move only in the X-Y directions, we can map the displacements of the feature points from a 2D video to a 3D face. These displacements are used to drive the Laplacian deformation and calculate the deformed positions of the non-feature points on the 3D face. The approach produces accurate, realistic and smooth transfer. Furthermore, the method is efficient and practical, and the interface is intuitive. The proposed technique outperforms previous methods based on machine learning and anatomy in terms of speed and applicability. Our method is useful for a wide range of applications, such as, avatars, character animation for 3D films, computer games, and online chatting. The versatility of our approach is demonstrated by some special effects, such as expression exaggeration and expression imitation.