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177:.) This is also a reason why 3D face recognition methods have emerged significantly later (in the late 1980s) than 2D methods. Recently 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
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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
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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
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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
349:; 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".
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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
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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.
173:. Alternatively, multiple images from different angles from a common camera (e.g. webcam) may be used to create the 3D model with significant post-processing. (See
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Queirolo, C. C.; Silva, L.; Bellon, O. R.; Segundo, M. P. (2009). "3D Face
Recognition using Simulated Annealing and the Surface Interpenetration Measure".
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Heseltine, T.; Pears, N.; Austin, J. (2008). "Three-dimensional face recognition using combinations of surface feature map subspace components".
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469:"Fast and Accurate 3D Face Recognition Using Registration to an Intrinsic Coordinate System and Fusion of Multiple Region classifiers"
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The main technological limitation of 3D face recognition methods is the acquisition of 3D image, which usually requires a
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Okuwobi, I. P.; Chen, Q; Niu S.; et al. (2016). "Three-dimensional (3D) facial recognition and prediction".
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Fast 3D scan technology for 3D face recognition at the
Geometric Modelling and Pattern Recognition Group, UK
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3D face recognition is still an active research field, though several vendors offer commercial solutions.
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3D Face
Recognition Using a Deformable Model at the Computational Biomedicine Lab, Houston, TX
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Bronstein, A. M.; Bronstein, M. M.; Kimmel, R. (2005). "Three-dimensional face recognition".
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Gupta, S.; Markey, M. K.; Bovik, A. C. (2010). "Anthropometric 3D Face
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Mitsubishi
Electric Research Laboratories 3D face recognition project
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Pattern Analysis and Machine Intelligence
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IEEE Transactions on
Pattern Analysis and Machine Intelligence
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as change in lighting, different facial expressions,
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http://paper.ijcsns.org/07_book/200912/20091222.pdf
538:L-1 Identity commercial 3D face recognition system
220:"Bioscrypt Introduces 3D Face Recognition Camera"
553:3D Face Recognition Using Photometric Stereo, UK
516:3D Face Recognition Project and Research Papers
175:3D data acquisition and object reconstruction
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104:It has been suggested that this article be
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69:Learn how and when to remove this message
501:CVPR 2008 Workshop on 3D Face Processing
473:International Journal of Computer Vision
401:International Journal of Computer Vision
288:International Journal of Computer Vision
32:This article includes a list of general
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521:Technion 3D face recognition project
259:Signal, Image and Video Processing
131:Three-dimensional face recognition
38:it lacks sufficient corresponding
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506:Face Recognition Grand Challenge
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121:Proposed since August 2024.
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16:Mode of facial recognition
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486:10.1007/s11263-011-0426-2
467:Spreeuwers, L.J. (2011).
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434:Spreeuwers, L.J. (2015).
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234:"Digiteyezer - iFace3D"
144:fingerprint recognition
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