A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Three-Dimensional Model Based Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Deformation Analysis for 3D Face Matching
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Integrating Range and Texture Information for 3D Face Recognition
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
3D face authentication by mutual coupled 3D and 2D feature extraction
Proceedings of the 44th annual Southeast regional conference
Robust face recognition from 2D and 3D images using structural Hausdorff distance
Image and Vision Computing
Face recognition using discriminant locality preserving projections
Image and Vision Computing
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Efficient 3D face recognition handling facial expression and hair occlusion
Image and Vision Computing
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This paper presents a novel method for automatic face authentication in which the variance of faces due to aging has been considered. A bilateral symmetrical plane is used for weighting the correspondences of the scanned model and database model upon model verification. This bilateral symmetrical plane is determined by the nose tip and two canthus features. The coupled 2D and 3D feature extraction method is introduced to determine the positions of these canthus features. The central profile on this bilateral symmetrical plane is the foundation of the face recognition. A weighting function is used to determine the rational points for the correspondences of the optimized iterative closest point method. The discrepancy value is evaluated for the authentication and compensation between different models. We have implemented this method on the practical authentication of human faces. The result illustrates that this method works well in both self authentication and mutual authentication.