NDLI: An Expression Deformation Approach to Non-rigid 3D Face Recognition

Content Provider	Springer Nature Link
Author	Al Osaimi, F. Bennamoun, M. Mian, A.
Copyright Year	2008
Abstract	The accuracy of non-rigid 3D face recognition approaches is highly influenced by their capacity to differentiate between the deformations caused by facial expressions from the distinctive geometric attributes that uniquely characterize a 3D face, interpersonal disparities. We present an automatic 3D face recognition approach which can accurately differentiate between expression deformations and interpersonal disparities and hence recognize faces under any facial expression. The patterns of expression deformations are first learnt from training data in PCA eigenvectors. These patterns are then used to morph out the expression deformations. Similarity measures are extracted by matching the morphed 3D faces. PCA is performed in such a way it models only the facial expressions leaving out the interpersonal disparities. The approach was applied on the FRGC v2.0 dataset and superior recognition performance was achieved. The verification rates at 0.001 FAR were 98.35% and 97.73% for scans under neutral and non-neutral expressions, respectively.
Starting Page	302
Ending Page	316
Page Count	15
File Format	PDF
ISSN	09205691
Journal	International Journal of Computer Vision
Volume Number	81
Issue Number	3
e-ISSN	15731405
Language	English
Publisher	Springer US
Publisher Date	2008-09-20
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	3D face recognition Expression invariance Non-rigid matching Pattern Recognition Image Processing and Computer Vision Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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