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Faces: Analysis and Synthesis. Vision for Graphics CSE 590SS, Winter 2001 Richard Szeliski. What can we do with faces?. Modeling (reconstruction): manual [Pighin et al. 1998] Automated [Zhang et al. 2000]. What can we do with faces?. Analysis
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Faces: Analysis and Synthesis Vision for GraphicsCSE 590SS, Winter 2001Richard Szeliski
What can we do with faces? • Modeling (reconstruction): • manual[Pighin et al. 1998] • Automated[Zhang et al. 2000] Vision for Graphics
What can we do with faces? • Analysis • principal components and deformation modes[Turk & Pentland 1991][Rowland & Perrett 1995][Guenter et al. 1998][Blanz & Vetter 1999] Vision for Graphics
What can we do with faces? • Tracking and synthesis • tracking[Toyama 1998] • animation[Pighin et al. 1999][Buck et al. 2000] • Recognition[Turk & Pentland 1991; Lanitis et al. 1997] Vision for Graphics
Synthesizing Realistic Facial Expressions from Photographs • Frederic Pighin Jamie Hecker Dani Lischinski v • David Salesin Richard Szeliski * • SIGGRAPH’98 Vision for Graphics
Animated Face Modeling From Video Images Zhengyou Zhang, Zicheng Liu, Michael Cohen Vision Group & Graphics Group Microsoft Research
Manipulating Facial Appearance through Shape and Color Duncan A. Rowland and David I. Perrett St Andrews University IEEE CG&A, September 1995
Principal component analysis • Compute average faces (color and shape) • Compute deviations between male and female (vector and color differences) Vision for Graphics
Deform shape and/or color of an input face in the direction of “more female” original shape color both Changing gender Vision for Graphics
Enhancing gender • more same original androgynous more opposite Vision for Graphics
Face becomes “rounder” and “more textured” and “grayer” original shape color both Changing age Vision for Graphics
A Morphable Model For The Synthesis Of 3D Faces Volker Blanz Thomas Vetter SIGGRAPH’99
Morphable model of 3D faces • Start with a catalogue of 200 3D Cyberware scans • Build a model of average shape and texture, and principal variations Vision for Graphics
Divide face into 4 regions (eyes, nose, mouth, head) For each new prototype, find amount of deviation from the reference shape and texture. Morphable model of 3D faces Vision for Graphics
Morphable model of 3D faces • Adding some variations Vision for Graphics
Reconstruction from single image Vision for Graphics
Modifying a single image Vision for Graphics
Animating from a single image Vision for Graphics
Resulting animation Vision for Graphics
Tracking Face Orientation Kentaro Toyama Vision–Based Interaction Group Microsoft Research
Resynthesizing Facial Animation through 3D Model-Based Tracking • Frédéric Pighin1 Richard Szeliski2 David Salesin1,2 1University of Washington 2Microsoft Research ICCV’99 Vision for Graphics
Performance-Driven Hand-Drawn Animation Ian Buck Adam Finkelstein Charles Jacobs Allison Klein David H. Salesin Joshua Seims Richard Szeliski Kentaro Toyama
Go from video to “cartoon” Vision for Graphics
Hand-drawn expressions Vision for Graphics
Expression correspondence Vision for Graphics
Morphing and tracking Vision for Graphics
More examples Vision for Graphics
Final animations Vision for Graphics
Bibliography • F. Pighin, J. Hecker, D. Lischinski, D. H. Salesin, and R. Szeliski. Synthesizing realistic facial expressions from photographs. In SIGGRAPH'98 Proceedings, pages 75--84, Orlando, July 1998. • Z. Liu, Z. Zhang, C. Jacobs, and M. Cohen. Rapid modeling of animated faces from video. Technical Report MSR-TR-2000-11, Microsoft Research, February 2000. • B. Guenter et al. Making faces. Proceedings of SIGGRAPH 98, pages 55--66, July 1998. • V. Blanz and T. Vetter. A morphable model for the synthesis of 3d faces. Proceedings of SIGGRAPH 99, pages 187--194, August 1999. • K. Toyama. Prolegomena for robust face tracking. Technical Report MSR-TR-98-65, Microsoft Research, November 1998. • F. Pighin, D. H. Salesin, and R. Szeliski. Resynthesizing facial animation through 3D model-based tracking. In Seventh International Conference on Computer Vision (ICCV'99), pages 143--150, Kerkyra, Greece, September 1999. Vision for Graphics
Bibliography • I. Buck et al. Performance-driven hand-drawn animation. In Symposium on Non Photorealistic Animation and Rendering, pages 101--108, Annecy, June 2000. ACM SIGGRAPH. • D. A. Rowland and D. I. Perrett. Manipulating facial appearance through shape and color. IEEE Computer Graphics and Applications, 15(5):70--76, September 1995. • M. Turk and A. Pentland. Face recognition using eigenfaces. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'91), pages 586--591, Maui, Hawaii, June 1991. IEEE Computer Society Press. • P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):711--720, July 1997. • A. Lanitis, C. J. Taylor, and T. F. Cootes. Automatic interpretation and coding of face images using flexible models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):742--756, July 1997. Vision for Graphics