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Generalised Perspective Shape from Shading in Spherical Coordinates

  • Conference paper
Scale Space and Variational Methods in Computer Vision (SSVM 2013)

Abstract

In the last four decades there has been enormous progress in Shape from Shading (SfS) with respect to both modelling and numerics. In particular approaches based on advanced model assumptions such as perspective cameras and non-Lambertian surfaces have become very popular. However, regarding the positioning of the light source, almost all recent approaches still follow the simplest geometric configuration one can think of: The light source is assumed to be located exactly at the optical centre of the camera. In our paper, we refrain from this unrealistic and severe restriction. Instead we consider a much more general SfS scenario based on a perspective camera, where the light source can be positioned anywhere in the scene. To this end, we propose a novel SfS model that is based on a Hamilton-Jacobi equation (HJE) which in turn is formulated in terms of spherical coordinates. This particular choice of the modelling framework and the coordinate system comes along with two fundamental contributions: While on the modelling side, the spherical coordinate system allows us to derive a generalised brightness equation – a compact and elegant generalisation of the standard image irradiance equation to arbitrary configurations of the light source, on the numerical side, the formulation as Hamilton-Jacobi equation enables us to develop a specifically tailored variant of the fast marching (FM) method – one of the most efficient numerical solvers in the entire SfS literature. Results on synthetic and real-world data confirm our theoretical considerations. They clearly demonstrate the feasibility and efficiency of the generalised SfS approach.

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References

  1. Rindfleisch, T.: Photometric method for lunar topography. Photogrammetric Engineering 32, 262–277 (1966)

    Google Scholar 

  2. Horn, B.K.P.: Shape from shading: a method for obtaining the shape of a smooth opaque object from one view. PhD thesis. Massachusetts Institute of Technology (1970)

    Google Scholar 

  3. Ostrov, D.N.: Viscosity solutions and convergence of monotone schemes for synthetic aperture radar shape-from-shading equations with discontinuous intensities. SIAM Journal on Applied Mathematics 59, 2060–2085 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bors, A.G., Hancock, E.R., Wilson, R.C.: Terrain analysis using radar shape-from-shading. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 974–992 (2003)

    Article  Google Scholar 

  5. Abdelrahim, A.S., Abdelrahman, M.A., Abdelmunim, H., Farag, A., Miller, M.: Novel image-based 3D reconstruction of the human jaw using shape from shading and feature descriptors. In: Proceedings of the British Machine Vision Conference, pp. 1–11 (2011)

    Google Scholar 

  6. Okatani, T., Deguchi, K.: Shape reconstruction from an endoscope image by shape from shading technique for a point light source at the projection center. Computer Vision and Image Understanding 66, 119–131 (1997)

    Article  Google Scholar 

  7. Tankus, A., Sochen, N., Yeshurun, Y.: Perspective shape-from-shading by fast marching. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 43–49 (2004)

    Google Scholar 

  8. Wang, G.H., Han, J.Q., Zhang, X.M.: Three-dimensional reconstruction of endoscope images by a fast shape from shading method. Measurement Science and Technology 20 (2009)

    Google Scholar 

  9. Wu, C., Narasimhan, S., Jaramaz, B.: A multi-image shape-from-shading framework for near-lighting perspective endoscopes. International Journal of Computer Vision 86, 211–228 (2010)

    Article  MathSciNet  Google Scholar 

  10. Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.: Shape from shading: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence 21, 690–706 (1999)

    Article  Google Scholar 

  11. Durou, J.D., Falcone, M., Sagona, M.: Numerical methods for shape-from-shading: A new survey with benchmarks. Computer Vision and Image Understanding 109, 22–43 (2008)

    Article  Google Scholar 

  12. Prados, E., Faugeras, O.: Shape from shading: A well-posed problem? In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 870–877 (2005)

    Google Scholar 

  13. Courteille, F., Crouzil, A., Durou, J.D., Gurdjos, P.: Towards shape from shading under realistic photographic conditions. In: IEEE International Conference on Pattern Recognition, vol. 2, pp. 277–280 (2004)

    Google Scholar 

  14. Tankus, A., Sochen, N., Yeshurun, Y.: Shape-from-shading under perspective projection. International Journal of Computer Vision 63, 21–43 (2005)

    Article  Google Scholar 

  15. Bruvoll, S., Reimers, M.: Spherical surface parameterization for perspective shape from shading. Pattern Recognition Letters 33, 33–40 (2012)

    Article  Google Scholar 

  16. Ahmed, A., Farag, A.: A new formulation for shape from shading for non-Lambertian surfaces. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1817–1824 (2006)

    Google Scholar 

  17. Vogel, O., Breuß, M., Weickert, J.: Perspective shape from shading with non-lambertian reflectance. In: Rigoll, G. (ed.) DAGM 2008. LNCS, vol. 5096, pp. 517–526. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  18. Rouy, E., Tourin, A.: A viscosity solutions approach to shape-from-shading. SIAM Journal on Numerical Analysis 29, 867–884 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  19. Crandall, M., Lions, P.L.: Viscosity solutions of Hamilton-Jacobi equations. Transactions of the American Mathematical Society 277, 1–42 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  20. Horn, B., Brooks, M.: The variational approach to shape from shading. Computer Vision, Graphics, and Image Processing 33, 174–208 (1986)

    Article  MATH  Google Scholar 

  21. Alkhalifah, T., Fomel, S.: Implementing the fast marching eikonal solver: spherical versus Cartesian coordinates. Geophysical Prospecting 49, 165–178 (2001)

    Article  Google Scholar 

  22. Sethian, J.: A fast marching level set method for monotonically advancing fronts. Proc. of the National Academy of Sciences of the United States of America, 1591–1595 (1995)

    Google Scholar 

  23. Sethian, J.: Fast-marching level-set methods for three-dimensional photolithography development. In: Proc. SPIE, Optical Microlithography IX., vol. 2726, pp. 262–272 (1996)

    Google Scholar 

  24. Sethian, J.: Level set methods and fast marching methods. Cambridge University Press (1999)

    Google Scholar 

  25. Tsitsiklis, J.: Efficient algorithms for globally optimal trajectories. IEEE Transactions on Automatic Control 40, 1528–1538 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  26. Helmsen, J., Puckett, E., Colella, P., Dorr, M.: Two new methods for simulating photolithography development in 3D. In: Proc. SPIE, Optical Microlithography IX, vol. 2726, pp. 253–261 (1996)

    Google Scholar 

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Galliani, S., Ju, Y.C., Breuß, M., Bruhn, A. (2013). Generalised Perspective Shape from Shading in Spherical Coordinates. In: Kuijper, A., Bredies, K., Pock, T., Bischof, H. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2013. Lecture Notes in Computer Science, vol 7893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38267-3_19

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  • DOI: https://doi.org/10.1007/978-3-642-38267-3_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38266-6

  • Online ISBN: 978-3-642-38267-3

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