Integration of local and global geometrical cues for 3D face recognition
Pattern Recognition
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keypoint Detection and Local Feature Matching for Textured 3D Face Recognition
International Journal of Computer Vision
An Expression Deformation Approach to Non-rigid 3D Face Recognition
International Journal of Computer Vision
A 3D face matching framework for facial curves
Graphical Models
Binary neural network based 3D facial feature localization
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Proceedings of the ACM workshop on 3D object retrieval
Face recognition using 2d and 3d multimodal local features
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Keypoint identification and feature-based 3D face recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Random Forests for Real Time 3D Face Analysis
International Journal of Computer Vision
A Machine-Learning Approach to Keypoint Detection and Landmarking on 3D Meshes
International Journal of Computer Vision
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A fully automatic 3D face recognition algorithm is presented. Several novelties are introduced to make the recognition robust to facial expressions and efficient. These novelties include: (1) Automatic 3D face detection by detecting the nose; (2) Automatic pose correction and normalization of the 3D face as well as its corresponding 2D face using the Hotelling Transform; (3) A Spherical Face Representation and its use as a rejection classifier to quickly reject a large number of candidate faces for efficient recognition; and (4) Robustness to facial expressions by automatically segmenting the face into expression sensitive and insensitive regions. Experiments performed on the FRGC Ver 2.0 dataset (9,500 2D/3D faces) show that our algorithm outperforms existing 3D recognition algorithms. We achieved verification rates of 99.47% and 94.09% at 0.001 FAR and identification rates of 98.03% and 89.25% for probes with neutral and non-neutral expression respectively.