Computational Models for Animating 3D Virtual Faces

Automatic synthesis of facial animation in Computer Graphics is a challenging task and although the problem is three decades old by now, there is still not a unified method to solve it. This is mainly due to the complex mathematical model required to reproduce the visual meanings of facial expressions coupled with the computational speed needed to run interactive applications. In this thesis, there are two different proposed methods to address the problem of the realistic animation of 3D virtual faces at interactive rate. The first method is an integrated physically-based method which mimics the facial movements by reproducing the musculoskeletal structure of a human head and the interaction among the bony structure, the facial muscles and the skin. Differently from previously proposed approaches in the literature, the muscles are organized in a layered, interweaving structure laying on the skull; their shape is affected both by the simulation of active contraction and by the motion of the underlying anatomical parts. A design tool has been developed in order to assist the user in defining the muscles in a natural manner by sketching their shape directly on top of the already existing bones and other muscles. The dynamics of the face motion is computed through a position-based schema ensuring real-time performance, control and robustness. Experiments demonstrate that through this model it is possible to effectively synthesize realistic expressive facial animation on different input face models in real-time on consumer class platforms. The second method for automatically achieving animation consists of a novel facial motion cloning technique. This is a purely geometric algorithm and it is able to transfer the motion from an animated source face to a different target face mesh, initially static, allowing to reuse facial motion from already animated virtual heads. Its robustness and flexibility are assessed over several input data sets.