| E. Prados, O. Faugeras & E. Rouy, Shape from Shading and Viscosity Solutions, In Proc. of European Conference on Computer Vision 2002, 790-804 |
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. Technical Report 4638, INRIA, November 2002.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In Proceedings of ECCV'02, LNCS,volume 2351, pages 790804, May 2002.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In A. Heyden, G. Sparr, M. Nielsen, and P. Johansen, editors, Proceedings of the 7th European Conference on Computer Vision, volume 2351, pages 790--804, Copenhagen, Denmark, May 2002. Springer--Verlag.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In A. Heyden, G. Sparr, M. Nielsen, and P. Johansen, editors, Proceedings of the 7th European Conference on Computer Vision, volume 2351, pages 790--804, Copenhagen, Denmark, May 2002. Springer--Verlag.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In A. Heyden, G. Sparr, M. Nielsen, and P. Johansen, editors, Proceedings of the 7th European Conference on Computer Vision, volume 2351, pages 790--804, Copenhagen, Denmark, May 2002. Springer-- Verlag.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. Technical Report 4638, INRIA, Nov. 2002.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In Proceedings of ECCV'02, June 2002.
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. Technical report, INRIA, 2002.
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E. Prados, O. Faugeras, and E. Rouy. Shape from Shading and viscosity solutions. In Proceedings of ECCV'02, volume 2351, pages 790--804, May 2002.
....image restoration, shapes modeled with 3D surfaces can be simplified by regularization PDE s. There are for instance applications in medical imaging, by studying the particular structures of biological objects (for instance the brain, as illustrated in Fig.1. 8b and [93] a) Shape from shading [149] (b) Brain model simplification [87, 93] Figure 1.8: Two other computer vision problems, treated as 3D surface evolutions. This application list is obviously incomplete, but it illustrates the high interest in PDE based methods in computer vision and the large number of applications that ....
E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In Proceedings of ECCV'02, June 2002.
....of it. It is possible if one looks at the intensity variations of the image pixels due to the shadows and the different illumination conditions during the snapshot. PDE s can describe the flow of an originally flat 3D surface converging to the 3D shape of the real object (Fig.1. 8a) See [95, 96, 148] for a nice panorama of the research in this area. Shape simplification : Like image restoration, shapes modeled with 3D surfaces can be simplified by regularization PDE s. There are for instance applications in medical imaging, by studying the particular structures of biological objects (for ....
E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. Technical report, INRIA, 2002.
....methods to more realistic scenes. Third, it allows us to produce an approximation scheme for computing approximations of the continuous solution on a discrete grid as well as a proof of their convergence toward that solution. This report aims to deepen the notions presented in our article [28]. Here we give the proofs of the theorems proposed in [28] and which don t appear in other references. Finally by this text, we want to popularize the notion of viscosity solutions and make it more intuitive. Also we hope to convince the reader of the usability of these tools. ....
....to produce an approximation scheme for computing approximations of the continuous solution on a discrete grid as well as a proof of their convergence toward that solution. This report aims to deepen the notions presented in our article [28] Here we give the proofs of the theorems proposed in [28] and which don t appear in other references. Finally by this text, we want to popularize the notion of viscosity solutions and make it more intuitive. Also we hope to convince the reader of the usability of these tools. http: www sop.inria.fr odyssee team Emmanuel.Prados ....
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E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. In Proceedings of ECCV'02, June 2002.
.... d = t u(x (0; 15) and I(x) then T ( x; t; u) I(x) 3. If x2[ then T ( x; t; u) t (x) 16) We have noted = fx 2 jx ( 0) x ( 0) x (0; x (0; g and . 6. 2 Convergence of the approximation scheme The following theorem is proved in [23]: Theorem 5 Let T ( x; t; u) 0 be an approximation scheme which can be written as g(x; a; b; c; d) 0, where a; b; c; d are de ned in (15) Let us assume that the approximation scheme S satis es the hypotheses MSC (de ned below) then for all positive , the scheme has a solution noted ....
....y (x) H(x; x) r (x) Let us emphasize the fact that when the scheme is obtained by the process described in subsection 6.1, most MSC hypotheses are systematically veri ed. In particular, it is easily to apply the theorem 5, in the case for all x (x) For more details, see [23]. 6.3 Algorithm for computing the solution Thanks to theorem 5, we know that when = x; y) tends to zero, the solutions u of the numerical scheme (13) converge to the unique viscosity solution of equation (8) We now describe an algorithm that computes an approximation of u , for each ....
E. Prados, O. Faugeras, and E. Rouy. Shape from shading and viscosity solutions. Technical report, INRIA, 2002.
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E. Prados, O. Faugeras & E. Rouy, Shape from Shading and Viscosity Solutions, In Proc. of European Conference on Computer Vision 2002, 790-804
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