Behavioral Animation of Faces: Parallel, Distributed, and Real-Time

Facial animation has a lengthy history in computer graphics. To date, most efforts have concentrated either on labor-intensive keyframe schemes, on manually animated parameterized methods using FACS-inspired expression control schemes, or on performance-based animation where facial motions are captured from human actors. As an alternative, we propose the fully automated animation of faces using behavioral animation methods. To this end, we employ a physics-based model of the face, which includes synthetic facial soft tissues with embedded muscle actuators. Despite its technical sophistication, this biomechanical face model can nonetheless be simulated in real time on a high-end personal computer. The model incorporates a motor control layer that automatically coordinates eye and head movements, as well as muscle contractions to produce natural expressions. Utilizing principles from artificial life, we augment the synthetic face with a perception model that affords it a visual awareness of its environment, and we provide a sensorimotor response mechanism that links percepts to meaningful actions (i.e., head/eye movement and facial expression). The latter is implemented as an ethologically inspired behavioral repertoire, which includes a rudimentary emotion model. We demonstrate a networked, multi-computer implementation of our behavioral facial animation framework. Each of several faces is computed in real time by a separate server PC which transmits its simulation results to a client PC dedicated to rendering the animated faces in a common virtual space. Performing the appropriate head/eye/face movements, the autonomous faces look at one another and respond in a natural manner to each other’s expressions.