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We present a model-based approach to recover the rigid and non-rigid facial motion parameters in video sequences. Our face model is based on anatomically motivated muscle actuator controls to model the articulated non-rigid motion of a human face. The model is capable of generating a variety of facial expressions by using a small number of muscle actuator controls. We estimate rigid and non-rigid parameters in two steps. First, we use a multi-resolution scheme to recover the global 3D rotation and translation by linear least square minimization. Then, we estimate the muscle actuator controls using the Levenberg-Marquardt minimization technique applied to a function, which is constrained by both optical flow and the dynamics of the deformable model. We present the results of our system on both real and synthetic images.

Associated publications:
Alper Yilmaz, Khurram Hassan Shafique; Estimation of rigid and non-rigid facial motion using anatomical face model, International Conference on Pattern Recognition, August 11-15 2002 - Québec City Convention Center