3D face recognition by constructing deformation invariant image
Pattern Recognition Letters
Elastic Shape Models for Face Analysis Using Curvilinear Coordinates
Journal of Mathematical Imaging and Vision
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
3D face reconstructions from photometric stereo using near infrared and visible light
Computer Vision and Image Understanding
Elastic radial curves to model 3D facial deformations
Proceedings of the ACM workshop on 3D object retrieval
Computer Vision and Image Understanding
2.5D face recognition using Patch Geodesic Moments
Pattern Recognition
Isometric deformation invariant 3D shape recognition
Pattern Recognition
On the simultaneous recognition of identity and expression from BU-3DFE datasets
Pattern Recognition Letters
3D human face description: landmarks measures and geometrical features
Image and Vision Computing
Selecting 3D curves on the nasal surface using AdaBoost for person authentication
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
Geodesic Polar Coordinates on Polygonal Meshes
Computer Graphics Forum
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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.