COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Point Signatures: A New Representation for 3D Object Recognition
International Journal of Computer Vision
Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Radial Symmetry for Detecting Points of Interest
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel cubic-order algorithm for approximating principal direction vectors
ACM Transactions on Graphics (TOG)
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
3D Face Recognition Using Two Views Face Modeling and Labeling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Detection of Anchor Points for 3D Face Veri.cation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A Prescreener for 3D Face Recognition Using Radial Symmetry and the Hausdorff Fraction
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Matching 2.5D Face Scans to 3D Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Feature Extraction for Multiview 3D Face Recognition
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
Combining local features for robust nose location in 3D facial data
Pattern Recognition Letters
3D face detection using curvature analysis
Pattern Recognition
Automatic 3D facial segmentation and landmark detection
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Robust real-time 3D head pose estimation from range data
Pattern Recognition
From 3D Point Clouds to Pose-Normalised Depth Maps
International Journal of Computer Vision
Automatic 3d face feature points extraction with spin images
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
A structured template based 3D face recognition approach
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
An efficient 3D face recognition approach using local geometrical signatures
Pattern Recognition
A central profile-based 3D face pose estimation
Pattern Recognition
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Nose tip detection in range images is a specific facial feature detection problem that is highly important for 3D face recognition. In this paper, we propose a nose tip detection method that has the following three characteristics. First, it does not require training and does not rely on any particular model. Second, it can deal with both frontal and non-frontal poses. Finally, it is quite fast, requiring only seconds to process an image of 100-200 pixels (in both x and y dimensions) with a MATLAB implementation. A complexity analysis shows that most of the computations involved in the proposed algorithm are simple. Thus, if implemented in hardware (such as a GPU implementation), the proposed method should be able to work in real time. We tested the proposed method extensively on synthetic image data rendered by a 3D head model and real data using FRGC v2.0 data set. Experimental results show that the proposed method is robust to many scenarios that are encountered in common face recognition applications (e.g., surveillance). A high detection rate of 99.43% was obtained on FRGC v2.0 data set. Furthermore, the proposed method can be used to coarsely estimate the roll, yaw, and pitch angles of the face pose.