Active shape models—their training and application
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Coding Facial Expressions with Gabor Wavelets
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Face Shape Extraction and Recognition Using 3D Morphing and Distance Mapping
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
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The Active Appearance Model (AAM) is a powerful tool for modelling a class of objects such as faces. However, it is common to see a far from optimal local alignment when attempting to model a face that is quite different from training faces. In this paper, we present a novel component-based AAM algorithm. By modelling three components inside the face area, then combining them with a global AAM, face alignment achieves both local as well as global optimality. We also utilize local projection models to locate face contour points. Compared to the original AAM, our experiment shows that this new algorithm is more accurate in shape localization as the decoupling allows more flexibility. Its insensitivity to different face background patterns is also clearly manifested.