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Published Articles >> Table of Contents >> Abstract
16th International Conference on Pattern Recognition (ICPR'02) - Volume 1
p. 10377
Estimation of Rigid and Non-Rigid Facial Motion Using Anatomical Face Model
Alper Yilmaz, University of Central Florida
Khurram Shafique, University of Central Florida
Mubarak Shah, University of Central Florida
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2002.1044729
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| Abstract |
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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.
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 Additional Information
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Citation:
Alper Yilmaz, Khurram Shafique, Mubarak Shah,
"Estimation of Rigid and Non-Rigid Facial Motion Using Anatomical Face Model,"
icpr,
p. 10377,
16th International Conference on Pattern Recognition (ICPR'02) - Volume 1,
2002
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