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
Curvature approximation for triangulated surfaces
Geometric modelling
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
Expression-invariant 3D face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Automatic face authentication with self compensation
Image and Vision Computing
Partial matching of interpose 3D facial data for face recognition
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Automatic 3D facial region retrieval from multi-pose facial datasets
EG 3DOR'09 Proceedings of the 2nd Eurographics conference on 3D Object Retrieval
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In this paper, we present a novel method for automatic 3D face authentication. We introduce a coupled 2D and 3D feature-extraction method to determine the positions of eye sockets. The nose tip is considered as the extreme vertex along the normal directions of eye sockets. Once the nose tip and eye sockets are found, the bilateral symmetrical plane will be determined. The central profile which is on the bilateral symmetrical plane is the foundation for recognizing human face in our method. We use a weighting function for ICP according to the bilateral symmetrical behavior. We take 2.5D range image and its corresponding texture as the input data and compare the scanned model with the specified database model. The value of the weighted distance between two compared models is used for authentication. We have successively implemented this method for the authentication of the human faces. The result illustrates that this method work well in self authentication.