A facial motion tracking and transfer method based on a key point detection

Abstract

Facial animation is one of the most important contents in 3D CG animations. By the development of scanning and tracking methods of a facial motion, a face model which consists of more than 100,000 points can be used for the animations. To edit the facial animations, key point based approaches such as "face rigging" are still useful ways. Even if a facial tracking method gives us all point-to-point correspondences, a detection method of a suitable set of key points is needed for content creators. Then, we propose a method to detect the key points which efficiently represent motions of a face. We optimize the key points for a Radial Basis Function (RBF) based 3D deformation technique. The RBF based deformation is a common technique to represent a movement of 3D objects in CG animations. Since the key point based approaches usually deform objects by interpolating movements of the key points, these approaches cause errors between the deformed shapes and the original ones. To minimize the errors, we propose a method which automatically inserts additional key points by detecting the area where the error is larger than the surrounding area. Finally, by utilizing the suitable set of key points, the proposed method creates a motion of a face which are transferred form another motion of a face.