Computer graphics (2nd ed. in C): principles and practice
Computer graphics (2nd ed. in C): principles and practice
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
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-Dimensional Face Recognition Using Shapes of Facial Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering Facial Shape Using a Statistical Model of Surface Normal Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial Shape-from-shading and Recognition Using Principal Geodesic Analysis and Robust Statistics
International Journal of Computer Vision
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Robust 3D Face Recognition by Local Shape Difference Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Face Recognition Using Isogeodesic Stripes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Facial Symmetry to Handle Pose Variations in Real-World 3D Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Region Ensemble for 3-D Face Recognition
IEEE Transactions on Information Forensics and Security
Representation Plurality and Fusion for 3-D Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Expression-Invariant Representations of Faces
IEEE Transactions on Image Processing
Subspace Learning from Image Gradient Orientations
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We introduce novel subspace-based methods for learning from the azimuth angle of surface normals for 3D face recognition. We show that the normal azimuth angles combined with Principal Component Analysis (PCA) using a cosine-based distance measure can be used for robust face recognition from facial surfaces. The proposed algorithms are well-suited for all types of 3D facial data including data produced by range cameras (depth images), photometric stereo (PS) and shade-from-X (SfX) algorithms. We demonstrate the robustness of the proposed algorithms both in 3D face reconstruction from synthetically occluded samples, as well as, in face recognition using the FRGC v2 3D face database and the recently collected Photoface database where the proposed method achieves state-of-the-art results. An important aspect of our method is that it can achieve good face recognition/verification performance by using raw 3D scans without any heavy preprocessing (i.e., model fitting, surface smoothing etc.).