Combining Models and Exemplars for Face Recognition: An Illuminating Example

We propose a model- and exemplar-based approach for face recognition. This problem has been previously tackled using either models or exemplars, with limited success. Our idea uses models to synthesize many more exemplars, which are then used in the learning stage of a face recognition system. To demonstrate this, we develop a statistical shape-fromshading model to recover face shape from a single image, and to synthesize the same face under new illumination. We then use this to build a simple and fast classifier that was not possible before because of a lack of training data.

[1]  Rama Chellappa,et al.  Estimation of illuminant direction, albedo, and shape from shading , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[3]  A. Kuijpers-Jagtman.  [Illuminating the face]. , 1993, Nederlands tijdschrift voor tandheelkunde.

[4]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[5]  Learning Object Representations from LightingVariationsR , 1996 .

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

[7]  B. S. Manjunath,et al.  An Eigenspace Update Algorithm for Image Analysis , 1997, CVGIP Graph. Model. Image Process..

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

[9]  Timothy F. Cootes,et al.  Face Recognition Using Active Appearance Models , 1998, ECCV.

[10]  Chao Yang,et al.  ARPACK users' guide - solution of large-scale eigenvalue problems with implicitly restarted Arnoldi methods , 1998, Software, environments, tools.

[11]  D. B. Graham,et al.  Face recognition from unfamiliar views: subspace methods and pose dependency , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.

[12]  Rama Chellappa,et al.  Robust Face Recognition Using Symmetric Shape-from-Shading , 1999 .

[13]  Amnon Shashua,et al.  The quotient image: Class based recognition and synthesis under varying illumination conditions , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[14]  Ping-Sing Tsai,et al.  Shape from Shading: A Survey , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  David J. Kriegman,et al.  From few to many: generative models for recognition under variable pose and illumination , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[16]  Rahul Sukthankar,et al.  Memory-based face recognition for visitor identification , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[17]  Rama Chellappa,et al.  Illumination-insensitive face recognition using symmetric shape-from-shading , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[18]  David G. Stork,et al.  Pattern classification, 2nd Edition , 2000 .

[19]  Takeo Kanade,et al.  Hallucinating faces , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[20]  Yanxi Liu,et al.  Facial Asymmetry: A New Biometric , 2001 .

[21]  Rahul Sukthankar,et al.  Argus: the digital doorman , 2001, IEEE Intelligent Systems.

[22]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.