A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition based on 3D ridge images obtained from range data
Pattern Recognition
An Expression Deformation Approach to Non-rigid 3D Face Recognition
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
A Framework for Long Distance Face Recognition Using Dense - and Sparse-Stereo Reconstruction
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Hybrid face recognition based on real-time multi-camera stereo-matching
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Ultra fast GPU assisted face recognition based on 3d geometry and texture data
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Distinguishing Facial Features for Ethnicity-Based 3D Face Recognition
ACM Transactions on Intelligent Systems and Technology (TIST)
Face recognition by SVMs classification and manifold learning of 2D and 3D radial geodesic distances
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
3D facial landmark localization via a local surface descriptor HoSNI
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
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This paper addresses 3D face recognition from facial shape. Firstly, we present an effective method to automatically extract ROI of facial surface, which mainly depends on automatic detection of facial bilateral symmetry plane and localization of nose tip. Then we build a reference plane through the nose tip for calculating the relative depth values. Considering the non-rigid property of facial surface, the ROI is triangulated and parameterized into an isomorphic 2D planar circle, attempting to preserve the intrinsic geometric properties. At the same time the relative depth values are also mapped. Finally we perform eigenface on the mapped relative depth image. The entire scheme is insensitive to pose variance. The experiment using FRGC database v1.0 obtains the rank-1 identification score of 95%, which outperforms the result of the PCA base-line method by 4%, which demonstrates the effectiveness of our algorithm.