Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
Model-based registration of front- and backviews of rotationally symmetric objects
Computer Vision and Image Understanding - Registration and fusion of range images
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Depth vs. Intensity: Which is More Important for Face Recognition?
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Three-Dimensional Model Based Face Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
2D and 3D face recognition: A survey
Pattern Recognition Letters
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
Deformation Modeling for Robust 3D Face Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Automatic 3D face recognition from depth and intensity Gabor features
Pattern Recognition
Sparsity preserving projections with applications to face recognition
Pattern Recognition
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
3D Face Recognition Using Simulated Annealing and the Surface Interpenetration Measure
IEEE Transactions on Pattern Analysis and Machine Intelligence
SVM-based feature extraction for face recognition
Pattern Recognition
Robust 3D Face Recognition by Local Shape Difference Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Anthropometric 3D Face Recognition
International Journal of Computer Vision
A training-free nose tip detection method from face range images
Pattern Recognition
3D Face Recognition Using Isogeodesic Stripes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel SVM+NDA model for classification with an application to face recognition
Pattern Recognition
A Region Ensemble for 3-D Face Recognition
IEEE Transactions on Information Forensics and Security
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Independent component analysis of Gabor features for face recognition
IEEE Transactions on Neural Networks
Spatially Optimized Data-Level Fusion of Texture and Shape for Face Recognition
IEEE Transactions on Image Processing
Selecting 3D curves on the nasal surface using AdaBoost for person authentication
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
Iterative Closest Normal Point for 3D Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents a computationally efficient 3D face recognition system based on a novel facial signature called Angular Radial Signature (ARS) which is extracted from the semi-rigid region of the face. Kernel Principal Component Analysis (KPCA) is then used to extract the mid-level features from the extracted ARSs to improve the discriminative power. The mid-level features are then concatenated into a single feature vector and fed into a Support Vector Machine (SVM) to perform face recognition. The proposed approach addresses the expression variation problem by using facial scans with various expressions of different individuals for training. We conducted a number of experiments on the Face Recognition Grand Challenge (FRGC v2.0) and the 3D track of Shape Retrieval Contest (SHREC 2008) datasets, and a superior recognition performance has been achieved. Our experimental results show that the proposed system achieves very high Verification Rates (VRs) of 97.8% and 88.5% at a 0.1% False Acceptance Rate (FAR) for the ''neutral vs. nonneutral'' experiments on the FRGC v2.0 and the SHREC 2008 datasets respectively, and 96.7% for the ROC III experiment of the FRGC v2.0 dataset. Our experiments also demonstrate the computational efficiency of the proposed approach.