3D Face Recognition with Geometrically Localized Surface Shape Indexes

This paper describes a pose invariant three-dimensional (3D) face recognition method using distinctive facial features. A face has its structural components like the eyes, nose and mouth. The positions and the shapes of the facial components are very important characteristics of a face. We extract invariant facial feature points on those components using the facial geometry from a normalized face data and calculate relative features using these feature points. We also calculate a shape index on each area of facial feature point to represent curvature characteristics of facial components. We perform recognition by using weighted distance matching, support vector machine (SVM) and independent component analysis (ICA)

[1]  Anil K. Jain,et al.  Three-dimensional model based face recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[2]  Ronald-Bryan O. Alferez,et al.  Geometric and Illumination Invariants for Object Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Maja Pantic,et al.  Automatic Analysis of Facial Expressions: The State of the Art , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Thomas Vetter,et al.  Face Recognition Based on Fitting a 3D Morphable Model , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Patrick J. Flynn,et al.  A survey of approaches to three-dimensional face recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[6]  Shimon Ullman,et al.  Face Recognition: The Problem of Compensating for Changes in Illumination Direction , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Guodong Guo,et al.  Face recognition by support vector machines , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[8]  Patrick J. Flynn,et al.  A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition , 2006, Comput. Vis. Image Underst..

[9]  Anil K. Jain,et al.  Matching 2.5D Scans for Face Recognition , 2004, ICBA.

[10]  Tomaso A. Poggio,et al.  Face recognition with support vector machines: global versus component-based approach , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[11]  Gérard G. Medioni,et al.  Object modeling by registration of multiple range images , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[12]  Alexander M. Bronstein,et al.  Three-Dimensional Face Recognition , 2005, International Journal of Computer Vision.

[13]  Michael G. Strintzis,et al.  Use of depth and colour eigenfaces for face recognition , 2003, Pattern Recognit. Lett..

[14]  Massimiliano Pontil,et al.  Support Vector Machines for 3D Object Recognition , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Kwanghoon Sohn,et al.  3D Face Recognition under Pose Varying Environments , 2003, WISA.

[16]  Chin-Seng Chua,et al.  Facial feature detection and face recognition from 2D and 3D images , 2002, Pattern Recognit. Lett..

[17]  Gaile G. Gordon,et al.  Face recognition based on depth maps and surface curvature , 1991, Optics & Photonics.

[18]  José F. Vélez,et al.  Face recognition using 3D surface extracted descriptors , 2003 .

[19]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[20]  J AtickJoseph,et al.  Statistical approach to shape from shading , 1996 .

[21]  Patrick J. Flynn,et al.  An evaluation of multimodal 2D+3D face biometrics , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Chitra Dorai,et al.  COSMOS - A Representation Scheme for 3D Free-Form Objects , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Tomaso A. Poggio,et al.  Linear Object Classes and Image Synthesis From a Single Example Image , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using orthonormal matrices , 1988 .

[25]  David J. Kriegman,et al.  What is the set of images of an object under all possible lighting conditions? , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[26]  Rama Chellappa,et al.  Human and machine recognition of faces: a survey , 1995, Proc. IEEE.

[27]  Norbert Krüger,et al.  Face recognition by elastic bunch graph matching , 1997, Proceedings of International Conference on Image Processing.

[28]  Rama Chellappa,et al.  A feature based approach to face recognition , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[29]  Ronen Basri,et al.  Comparing images under variable illumination , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[30]  Gordon Erlebacher,et al.  A novel technique for face recognition using range imaging , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[31]  Hyeonjoon Moon,et al.  The FERET evaluation methodology for face-recognition algorithms , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[32]  Gaile G. Gordon,et al.  Face recognition based on depth and curvature features , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[33]  Kwanghoon Sohn,et al.  3D Face Recognition Based on Facial Shape Indexes with Dynamic Programming , 2006, ICB.

[34]  P. Jonathon Phillips,et al.  Face recognition vendor test 2002 , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).

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

[36]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[37]  Xinhua Zhuang,et al.  Pose estimation from corresponding point data , 1989, IEEE Trans. Syst. Man Cybern..

[38]  Patrick J. Flynn,et al.  Face Recognition Using 2D and 3D Facial Data , 2003 .

[39]  BlanzVolker,et al.  Face Recognition Based on Fitting a 3D Morphable Model , 2003 .

[40]  Thomas S. Huang,et al.  Motion and structure from feature correspondences: a review , 1994, Proc. IEEE.

[41]  David J. Kriegman,et al.  Illumination-based image synthesis: creating novel images of human faces under differing pose and lighting , 1999, Proceedings IEEE Workshop on Multi-View Modeling and Analysis of Visual Scenes (MVIEW'99).

[42]  Horst Bunke,et al.  Face recognition using range images , 1997, Proceedings. International Conference on Virtual Systems and MultiMedia VSMM '97 (Cat. No.97TB100182).

[43]  Jaechang Shim,et al.  3D Face Recognition using Statistical Multiple Features for the Local Depth Information , 2003 .

[44]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.