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Estimation of Rigid and Non-rigid Facial Motion Using Anatomical Face Model

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.


Related Publication

Alper Yilmaz and 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