Active shape models—their training and application
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Active blobs: region-based, deformable appearance models
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Active Appearance Models Revisited
International Journal of Computer Vision
2D vs. 3D Deformable Face Models: Representational Power, Construction, and Real-Time Fitting
International Journal of Computer Vision
A Generative Shape Regularization Model for Robust Face Alignment
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Real-Time 3D Face and Facial Action Tracking Using Extended 2D+3D AAMs
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
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In this paper, a joint active appearance model (joint-AAM) framework is proposed for face alignment. The object function consists of more than one active appearance model and some constraint items. It can be optimized through the efficient project-out inverse compositional (POIC) fitting algorithm. By transferring the low dimensional parameter space to the high one, the facial shape can be converged to the acceptable solution easier by joint-AAM comparing to single AAM, especially if the initial solutions locate on each side of the optimal solution. In multi-view case, different AAMs are jointed if the true view is far from the initial views. In single view case, different initial solutions of one AAM can be jointed to handle poor initialization or exaggerative expressions. Alternatively, 3D shape model is employed to impose stronger shape constraints on joint-AAM. A geometrical explanation is given to describe the reason of the robustness of the joint-AAM. The experiments demonstrate its accuracy, robustness and efficiency. The acronyms in this paper are listed in Tab. 1.