3-D Face Recognition With the Geodesic Polar Representation

The performance of automatic 3-D face recognition can be significantly improved by coping with the nonrigidity of the facial surface. In this paper, we propose a geodesic polar parameterization of the face surface. With this parameterization, the intrinsic surface attributes do not change under isom...

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Bibliographic Details
Published in:IEEE transactions on information forensics and security 2007-09, Vol.2 (3), p.537-547
Main Authors: Mpiperis, I., Malassiotis, S., Strintzis, M.G.
Format: Article
Language:English
Subjects:
Authentication
Biometrics
Classification
Computer information security
Face detection
Face recognition
Facial
Fingerprint recognition
geodesic polar coordinates
Image recognition
Informatics
Invariants
isometric mapping
Mouth
Parametrization
range images
Representations
Security
Telematics
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Summary:The performance of automatic 3-D face recognition can be significantly improved by coping with the nonrigidity of the facial surface. In this paper, we propose a geodesic polar parameterization of the face surface. With this parameterization, the intrinsic surface attributes do not change under isometric deformations and, therefore, the proposed representation is appropriate for expression-invariant 3-D face recognition. We also consider the special case of an open mouth that violates the isometry assumption and propose a modified geodesic polar parameterization that also leads to invariant representation. Based on this parameterization, 3-D face recognition is reduced to the classification of expression-compensated 2-D images that can be classified with state-of-the-art algorithms. Experimental results verify theoretical assumptions and demonstrate the benefits of the geodesic polar parameterization on 3-D face recognition.
ISSN:1556-6013
1556-6021
DOI:10.1109/TIFS.2007.902326