IEEE Transactions on Pattern Analysis and Machine Intelligence
An Expression Deformation Approach to Non-rigid 3D Face Recognition
International Journal of Computer Vision
Automatic 3D face recognition from depth and intensity Gabor features
Pattern Recognition
3D Signatures for Fast 3D Face Recognition
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Automatic facial expression recognition on a single 3D face by exploring shape deformation
MM '09 Proceedings of the 17th ACM international conference on Multimedia
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
A 3D face recognition algorithm based on nonuniform re-sampling correspondence
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
The 3D Chinese head and face modeling
Computer-Aided Design
Geometric graph comparison from an alignment viewpoint
Pattern Recognition
Computer Vision and Image Understanding
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This paper presents a 3D approach for recognizing faces based on Principal Component Analysis (PCA). The approach addresses the issue of proper 3D face alignment required by PCA for maximum data compression and good generalization performance for new untrained faces. This issue has traditionally been addressed by 2D data normalization, a step that eliminates 3D object size information important for the recognition process. We achieve correspondence of facial points by registering a 3D face to a scaled generic 3D reference face and subsequently perform a surface normal search algorithm. 3D scaling of the generic reference face is performed to enable better alignment of facial points while preserving important 3D size information in the input face. The benefits of this approach for 3D face recognition and dimensionality reduction have been demonstrated on components of the Face Recognition Grand Challenge (FRGC) database versions 1 and 2.