Three-dimensional face recognition (3D face recognition) is a modality of facial recognition methods in which the three-dimensional geometry of the human face is used. It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts, rivaling fingerprint recognition.
3D model of a human face
3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face. This avoids such pitfalls of 2D face recognition algorithms as change in lighting, different facial expressions, make-up and head orientation. Another approach is to use the 3D model to improve accuracy of traditional image based recognition by transforming the head into a known view. Additionally, most 3D scanners acquire both a 3D mesh and the corresponding texture. This allows combining the output of pure 3D matchers with the more traditional 2D face recognition algorithms, thus yielding better performance (as shown in ).
The main technological limitation of 3D face recognition methods is the acquisition of 3D image, which usually requires a range camera. Alternatively, multiple images from different angles from a common camera (e.g. webcam[1]) may be used to create the 3D model with significant post-processing. (See 3D data acquisition and object reconstruction.)[2] This is also a reason why 3D face recognition methods have emerged significantly later (in the late 1980s) than 2D methods. Recently[when?] commercial solutions have implemented depth perception by projecting a grid onto the face and integrating video capture of it into a high resolution 3D model. This allows for good recognition accuracy with low cost off-the-shelf components.
3D face recognition is still an active research field, though several vendors offer commercial solutions.
^Nirav Sanghani (March 28, 2007). "Bioscrypt Introduces 3D Face Recognition Camera". DailyTech.
^. Archived from the original on 2012-04-25. Retrieved 2011-11-07.
Okuwobi, I. P.; Chen, Q; Niu S.; et al. (2016). "Three-dimensional (3D) facial recognition and prediction". Signal, Image and Video Processing. 10 (6): 1151–1158. doi:10.1007/s11760-016-0871-z. S2CID 11211308.
Bronstein, A. M.; Bronstein, M. M.; Kimmel, R. (2005). "Three-dimensional face recognition". International Journal of Computer Vision. 64 (1): 5–30. CiteSeerX10.1.1.77.9592. doi:10.1007/s11263-005-1085-y. S2CID 670151.
Heseltine, T.; Pears, N.; Austin, J. (2008). "Three-dimensional face recognition using combinations of surface feature map subspace components". Image and Vision Computing. 26 (3): 382–396. doi:10.1016/j.imavis.2006.12.008.
Kakadiaris, I. A.; Passalis, G.; Toderici, G.; Murtuza, N.; Karampatziakis, N.; Theoharis, T. (2007). "3D face recognition in the presence of facial expressions: an annotated deformable model approach". IEEE Transactions on Pattern Analysis and Machine Intelligence. 13 (12).
Queirolo, C. C.; Silva, L.; Bellon, O. R.; Segundo, M. P. (2009). "3D Face Recognition using Simulated Annealing and the Surface Interpenetration Measure". IEEE Transactions on Pattern Analysis and Machine Intelligence. 32 (2): 206–19. doi:10.1109/TPAMI.2009.14. PMID 20075453. S2CID 12411479.
Gupta, S.; Markey, M. K.; Bovik, A. C. (2010). "Anthropometric 3D Face Recognition". International Journal of Computer Vision. 90 (3): 331–349. doi:10.1007/s11263-010-0360-8. S2CID 10679755.
A. Rashad, A Hamdy, M A Saleh and M Eladawy, "3D face recognition using 2DPCA", (IJCSNS) International Journal of Computer Science and Network Security,Vol.(12),2009. http://paper.ijcsns.org/07_book/200912/20091222.pdf
Spreeuwers, L.J. (2015). "Breaking the 99% barrier: optimisation of 3D face recognition". IET Biometrics. 4 (3): 169–177. doi:10.1049/iet-bmt.2014.0017. S2CID 195254.
Spreeuwers, L.J. (2011). "Fast and Accurate 3D Face Recognition Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region classifiers". International Journal of Computer Vision. 93 (3): 389–414. doi:10.1007/s11263-011-0426-2.
External linksedit
CVPR 2008 Workshop on 3D Face Processing
Face Recognition Homepage
3D Face Recognition Project and Research Papers
Technion 3D face recognition project
Mitsubishi Electric Research Laboratories 3D face recognition project 2006-11-09 at the Wayback Machine
3D Face Recognition Using Photometric Stereo, UK
May 04, 2024
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This article includes a list of general references but it lacks sufficient corresponding inline citations Please help to improve this article by introducing more precise citations November 2011 Learn how and when to remove this message Three dimensional face recognition 3D face recognition is a modality of facial recognition methods in which the three dimensional geometry of the human face is used It has been shown that 3D face recognition methods can achieve significantly higher accuracy than their 2D counterparts rivaling fingerprint recognition 3D model of a human face 3D face recognition has the potential to achieve better accuracy than its 2D counterpart by measuring geometry of rigid features on the face This avoids such pitfalls of 2D face recognition algorithms as change in lighting different facial expressions make up and head orientation Another approach is to use the 3D model to improve accuracy of traditional image based recognition by transforming the head into a known view Additionally most 3D scanners acquire both a 3D mesh and the corresponding texture This allows combining the output of pure 3D matchers with the more traditional 2D face recognition algorithms thus yielding better performance as shown in FRVT 2006 The main technological limitation of 3D face recognition methods is the acquisition of 3D image which usually requires a range camera Alternatively multiple images from different angles from a common camera e g webcam 1 may be used to create the 3D model with significant post processing See 3D data acquisition and object reconstruction 2 This is also a reason why 3D face recognition methods have emerged significantly later in the late 1980s than 2D methods Recently when commercial solutions have implemented depth perception by projecting a grid onto the face and integrating video capture of it into a high resolution 3D model This allows for good recognition accuracy with low cost off the shelf components 3D face recognition is still an active research field though several vendors offer commercial solutions See also edit3D object recognition Facial recognition systemReferences edit Nirav Sanghani March 28 2007 Bioscrypt Introduces 3D Face Recognition Camera DailyTech Digiteyezer iFace3D Archived from the original on 2012 04 25 Retrieved 2011 11 07 Okuwobi I P Chen Q Niu S et al 2016 Three dimensional 3D facial recognition and prediction Signal Image and Video Processing 10 6 1151 1158 doi 10 1007 s11760 016 0871 z S2CID 11211308 Bronstein A M Bronstein M M Kimmel R 2005 Three dimensional face recognition International Journal of Computer Vision 64 1 5 30 CiteSeerX 10 1 1 77 9592 doi 10 1007 s11263 005 1085 y S2CID 670151 Heseltine T Pears N Austin J 2008 Three dimensional face recognition using combinations of surface feature map subspace components Image and Vision Computing 26 3 382 396 doi 10 1016 j imavis 2006 12 008 Kakadiaris I A Passalis G Toderici G Murtuza N Karampatziakis N Theoharis T 2007 3D face recognition in the presence of facial expressions an annotated deformable model approach IEEE Transactions on Pattern Analysis and Machine Intelligence 13 12 Queirolo C C Silva L Bellon O R Segundo M P 2009 3D Face Recognition using Simulated Annealing and the Surface Interpenetration Measure IEEE Transactions on Pattern Analysis and Machine Intelligence 32 2 206 19 doi 10 1109 TPAMI 2009 14 PMID 20075453 S2CID 12411479 Gupta S Markey M K Bovik A C 2010 Anthropometric 3D Face Recognition International Journal of Computer Vision 90 3 331 349 doi 10 1007 s11263 010 0360 8 S2CID 10679755 A Rashad A Hamdy M A Saleh and M Eladawy 3D face recognition using 2DPCA IJCSNS International Journal of Computer Science and Network Security Vol 12 2009 http paper ijcsns org 07 book 200912 20091222 pdf Spreeuwers L J 2015 Breaking the 99 barrier optimisation of 3D face recognition IET Biometrics 4 3 169 177 doi 10 1049 iet bmt 2014 0017 S2CID 195254 Spreeuwers L J 2011 Fast and Accurate 3D Face Recognition Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region classifiers International Journal of Computer Vision 93 3 389 414 doi 10 1007 s11263 011 0426 2 External links editCVPR 2008 Workshop on 3D Face Processing Face Recognition Grand Challenge Face Recognition Homepage 3D Face Recognition Project and Research Papers Technion 3D face recognition project Mitsubishi Electric Research Laboratories 3D face recognition project Archived 2006 11 09 at the Wayback Machine L 1 Identity commercial 3D face recognition system Fast 3D scan technology for 3D face recognition at the Geometric Modelling and Pattern Recognition Group UK 3D Face Recognition Using a Deformable Model at the Computational Biomedicine Lab Houston TX 3D Face Recognition Using Photometric Stereo UK Retrieved from https en wikipedia org w index php title Three dimensional face recognition amp oldid 1206009822, wikipedia, wiki, book, books, library,
