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AUSAI
2006
Springer

3D Morphable Model Parameter Estimation

9 years 7 months ago
3D Morphable Model Parameter Estimation
Estimating the structure of the human face is a long studied and difficult task. In this paper we present a new method for estimating facial structure from only a minimal number of salient feature points. The presented method uses the Extended Kalman Filter (EKF) to regress 3D Morphable Model (3DMM) shape parameters and solve rigid body motion using a simplified camera model. A linear method for initializing the recursive filter is provided. The convergence properties of the method are then evaluated using synthetic data. The method is then demonstrated for both single image shape recovery and shape recovery during tracking.
Nathan Faggian, Andrew P. Paplinski, Jamie Sherrah
Added 13 Oct 2010
Updated 13 Oct 2010
Type Conference
Year 2006
Where AUSAI
Authors Nathan Faggian, Andrew P. Paplinski, Jamie Sherrah
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