A novel approach is presented to the analysis of dynamic facial images. The approach exploits a realistic model of the human face. The face model, which may be simulated and rendered at interactive rates on a graphics workstation, incorporates a physically-based approximation to facial tissue and a set of anatomically-motivated facial muscle actuators. The authors consider the estimation of dynamic facial muscle contractions from video sequences of expressive human faces. They develop an estimation technique that uses deformable contour models to track the nonrigid motions of facial features in images. The technique computes robust muscle actuator controls, enabling the face model to resynthesize transient expressions accurately.
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