Expression-Invariant 3D Face Recognition

We present a novel 3D face recognition approach based on geometric invariants introduced by Elad and Kimmel. The key idea of the proposed algorithm is a representation of the facial surface, invariant to isometric deformations, such as those resulting from different expressions and postures of the face. The obtained geometric invariants allow mapping 2D facial texture images into special images that incorporate the 3D geometry of the face. These signature images are then decomposed into their principal components. The result is an efficient and accurate face recognition algorithm that is robust to facial expressions. We demonstrate the results of our method and compare it to existing 2D and 3D face recognition algorithms.

[1]  A. Householder,et al.  Discussion of a set of points in terms of their mutual distances , 1938 .

[2]  Takeo Kanade,et al.  Computer recognition of human faces , 1980 .

[3]  Mikhael Gromov.  Structures métriques pour les variétés riemanniennes , 1981 .

[4]  Olivier D. Faugeras,et al.  A 3-D Recognition and Positioning Algorithm Using Geometrical Matching Between Primitive Surfaces , 1983, IJCAI.

[5]  Eric L. Schwartz,et al.  A Numerical Solution to the Generalized Mapmaker's Problem: Flattening Nonconvex Polyhedral Surfaces , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Paul J. Besl,et al.  The Free-Form Surface Matching Problem , 1990 .

[7]  Richard Szeliski,et al.  Recovering the Position and Orientation of Free-Form Objects from Image Contours Using 3D Distance Maps , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Gaile G. Gordon,et al.  Face recognition from frontal and profile views , 1995 .

[9]  James A. Sethian,et al.  Theory, algorithms, and applications of level set methods for propagating interfaces , 1996, Acta Numerica.

[10]  Patrick J. F. Groenen,et al.  Modern Multidimensional Scaling: Theory and Applications , 2003 .

[11]  David J. Kriegman,et al.  Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection , 1996, ECCV.

[12]  M. Sharir,et al.  Partial surface and volume matching in three dimensions , 1997 .

[13]  Marc Acheroy,et al.  Automatic Face Authentication from 3D surface , 1998, BMVC.

[14]  Brendan J. Frey,et al.  Mixtures of local linear subspaces for face recognition , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[15]  J A Sethian,et al.  Computing geodesic paths on manifolds. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Nahum Kiryati,et al.  Toward optimal structured light patterns , 1999, Image Vis. Comput..

[17]  Matthew Turk,et al.  A Morphable Model For The Synthesis Of 3D Faces , 1999, SIGGRAPH.

[18]  Alex Pentland,et al.  Bayesian face recognition , 2000, Pattern Recognit..

[19]  N. Mavridis,et al.  The HISCORE face recognition application : A ordable desktop face recognition based on a novel 3 D camera , 2001 .

[20]  Ron Kimmel,et al.  Computational Surface Flattening: A Voxel-Based Approach , 2001, IWVF.

[21]  Ron Kimmel,et al.  Bending invariant representations for surfaces , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[22]  Michael Elad,et al.  Content Based Retrieval of VRML Objects - An Iterative and Interactive Approach , 2001, Eurographics Multimedia Workshop.

[23]  Volker Blanz,et al.  Face Recognition Using Component-Based SVM Classification and Morphable Models , 2002, SVM.

[24]  Ron Kimmel,et al.  Computational Surface Flattening: A Voxel-Based Approach , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Michael Elad,et al.  Content based retrieval of VRML objects: an iterative and interactive approach , 2002 .

[26]  Ron Kimmel,et al.  Texture Mapping Using Surface Flattening via Multidimensional Scaling , 2002, IEEE Trans. Vis. Comput. Graph..

[27]  Ron Kimmel,et al.  On Bending Invariant Signatures for Surfaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..