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
COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
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
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Exploring facial expression effects in 3d face recognition using partial ICP
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
A Region Ensemble for 3-D Face Recognition
IEEE Transactions on Information Forensics and Security
Robust 3D face recognition from expression categorisation
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Gender classification using the profile
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Efficient 3D face recognition handling facial expression and hair occlusion
Image and Vision Computing
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We present an efficient 3D face recognition algorithm and demonstrate its performance on the FRGC v2.0 data set The pose of a 3D face is automatically corrected based on the nose tip and principle component analysis(PCA) The facial curve in the nose region is used to eliminate a large number of dissimilar faces in the gallery at an early stage Facial curves in the regions of forehead and cheeks are used to produce a mapping of facial deformation caused by expressions The remaining faces after rejection are then verified using a region-based matching approach This approach adaptively selects regions which are relatively steady based on the deformation mapping, and matches them separately At last, the results are fused using the sum rule Promising experimental results are achieved on FRGC v2.0 data set.