Abstract
This paper presents a novel algorithm aiming at analysis and identification of faces viewed from different poses and illumination conditions. Face analysis from a single image is performed by recovering the shape and textures parameters of a 3D Morphable Model in an analysis-by-synthesis fashion. The shape parameters are computed from a shape error estimated by optical flow and the texture parameters are obtained from a texture error. The algorithm uses linear equations to recover the shape and texture parameters irrespective of pose and lighting conditions of the face image. Identification experiments are reported on more than 5000 images from the publicly available CMU-PIE database which includes faces viewed from 13 different poses and under 22 different illuminations. Extensive identification results are available on our web page for future comparison with novel algorithms.
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References
Ronen Basri and David Jacobs. Lambertian reflectance and linear subspace. In 8th International Conference on Computer Vision, volume 2, pages 383–390, 2001.
J.R. Bergen and R. Hingorani. Hierarchical motion-based frame rate conversion. Technical report, David Sarnoff Research Center Princeton NJ 08540, 1990.
D. Beymer and T. Poggio. Image representation for visual learning. Science, 272, 1996.
D. M. Blackburn, M. Bone, and P. J. Phillips. Face recognition vendor test 2000: Evaluation report. Technical report, DoD Counterdrug Technology Development Program, 2000.
V. Blanz, S. Romdhani, and T. Vetter. Face identification across different poses and illuminations with a 3d morphable model. In Proc. of the 5th Int. Conf. on AFGR, 2002.
V. Blanz and T. Vetter. A morphable model for the synthesis of 3D-faces. In SIGGRAPH 99 Conference Proceedings, Los Angeles, 1999. Addison Wesley.
Volker Blanz. Automatische Rekonstruction der dreidimensionalen Form von Gesichtern aus einem Einzelbild. PhD thesis, Universitat Tübingen, Germany, 2001.
T. Cootes, G. Edwards, and C. Taylor. Active appearance model. In ECCV, 1998.
T. Cootes, K. Walker, and C. Taylor. View-based active appearance models, 2000.
T.F. Cootes, C.J. Taylor, D.H. Cooper, and J. Graham. Active shape models-their training and application. Computer Vision and Image Understanding, 1995.
J.D. Foley and A. vanDam. Fundamentals of interactive computer graphics. The systems programming series. Addison-Wesley, Reading, Ma, 1984.
M. Gleicher. Projective registration with difference decomposition, 1997.
Ralph Gross, Jianbo Shi, and Jeff Cohn. Quo vadis face recognition? In Third Workshop on Empirical Evaluation Methods in Computer Vision, 2001.
R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, 2000.
M. Jones and T. Poggio. Multidimensional morphable models: A framework for representing and matching object classes. In Proceedings of the Sixth ICCV, 1998.
P. J. Phillips, P. Rauss, and S. Der. Feret (face recognition technology) recognition algorithm development and test report. ARL-TR 995, U.S. Army Research Laboratory, 1996.
F. Pighin, R. Szeliski, and D.H. Salesin. Resynthesizing facial animation through 3d model-based tracking. In Proceedings of the 7th ICCV, pages 143–150, 1999.
Vetterling Press, Teukolsky and Flannery. Numerical recipes in C: the art of scientific computing. Cambridge University Press, Cambridge, 1992.
Ravi Ramamoorthi and Pat Hanrahan. A signal-processing framework for inverse rendering. In SIGGRAPH 2001 Conference Proceedings, pages 117–128, 2001.
S. Sclaroff and J. Isidoro. Active blobs. In 6th ICCV, 1998.
T. Sim, S. Baker, and M. Bsat. The cmu pose, illumination and expression (pie) database of human faces. Technical Report CMU-RI-TR-01-02, CMU, 2000.
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Romdhani, S., Blanz, V., Vetter, T. (2002). Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47979-1_1
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DOI: https://doi.org/10.1007/3-540-47979-1_1
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