An inverse dynamics approach to face animation

Muscle-based models of the human face produce high quality animation but re ly on recorded muscle activity signals or synthetic muscle signals that are often derived by trial and error. This paper presents a dynamic inversion of a muscle-based model (Lucero and Munhall, 1999) that permits the animati on to be created from kinematic recordings of facial movements. Using a non linear optimizer (Powell's algorithm), the inversion produces a muscle acti vity set for seven muscles in the lower face that minimize the root mean sq uare error between kinematic data recorded with OPTOTRAK and the correspond ing nodes of the modeled facial mesh. This inverted muscle activity is then used to animate the facial model. In three tests of the inversion, strong correlations were observed for kinematics produced from synthetic muscle ac tivity, for OPTOTRAK kinematics recorded from a talker for whom the facial model is morphologically adapted and finally for another talker with the mo del morphology adapted to a different individual. The correspondence betwee n the animation kinematics and the three-dimensional OPTOTRAK data are very good and the animation is of high quality. Because the kinematic to electr omyography (EMG) inversion is ill posed, there is no relation between the a ctual EMG and the inverted EMG. The overall redundancy of the motor system means that many different EMG patterns can produce the same kinematic outpu t. (C) 2001 Acoustical Society of America.