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
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Face Recognition Vendor Test 2002
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
A Fast Multi-Modal Approach to Facial Feature Detection
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
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
Journal of Cognitive Neuroscience
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Evaluation of 3d face recognition using registration and PCA
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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3D face data have the potential to improve the face recognition performance at disadvantageous conditions, such as uncontrolled illuminations, pose and expression. 3D nose tip location is the crucial step for registration and recognition of 3D face data. An automatic nose tip location and pose estimation method robust for pose changing at 3D face scans is proposed in this paper. We firstly gain some tip candidates by directional maximum and normalize the 3D scan data to front by hypothetical nose tips. Two filters respectively based on local structure of curves and PCA reconstruction curves errors are utilized to discard false tip candidates. The results of nose tip position and face recognition at BJUT 3D Database show the proposed method is efficient and robust for pose angle variety.