A face-to-muscle inversion of a biomechanical face model for audiovisual and motor control research

Abstract : Muscle-based models of the human face produce high quality animation but rely on recorded muscle activity signals or synthetic muscle signals often derived by trial and error. In this paper we present a dynamic inversion of a muscle-based model that permits the animation to be created from kinematic recordings of facial movements. Using a nonlinear optimizer (Powell's algorithm) the inversion produces a muscle activity set for 16 muscle groups in the lower face that minimize the root mean square error between kinematic data recorded with OPTOTRAK and the corresponding nodes of the modeled facial mesh. This inverted muscle activity is then used to animate the facial model. The results of a first experiment showed that the inversion-synthesis method can accurately reproduce a synthetic facial animation, even for a partial sampling of the face. The results of a second experiment showed that the method is as successful for OPTOTRAK recording of a talker uttering a sentence. The animation was of high quality.