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 survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Partial matching of interpose 3D facial data for face recognition
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Recognition of 3D faces with missing parts based on profile networks
Proceedings of the ACM workshop on 3D object retrieval
3D Face Recognition Using Isogeodesic Stripes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Region Ensemble for 3-D Face Recognition
IEEE Transactions on Information Forensics and Security
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In this work, we propose and experiment an original solution to 3D face recognition which supports partial matching of facial scans as occurs in the case of missing parts and occlusions. In the proposed approach, distinguishing traits of the face are captured by first extracting SIFT keypoints on the face scan and then measuring how the face changes along facial curves defined between pairs of keypoints. Facial curves are also associated with a measure of salience so as to distinguish curves that model characterizing traits of some subjects from curves that are frequently observed in the face of many different subjects. The recognition accuracy of the approach has been experimented on the Face Recognition Grand Challenge dataset.