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3-D Lighting Environment Estimation with Shading and Shadows

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Image and Geometry Processing for 3-D Cinematography

Part of the book series: Geometry and Computing ((GC,volume 5))

Abstract

We present a novel method for estimating 3-D lighting environments that consist of time-varying 3-D volumetric light sources from a single-viewpoint image. While various approaches for lighting environment estimation have been proposed, most of them assume the lighting environment as a distribution of directional light sources or a small number of near point light sources. Therefore, the estimation of a 3-D lighting environment still remains a challenging problem. In this paper, we propose a framework for estimating 3-D volumetric light sources, e.g. a frame of candles, using shadows cast on surfaces of a reference object by taking into account the geometric structures of the real world. We employ a combination of the Skeleton Cubes as a reference object and verify the utilities. We then describe how it works to estimate the 3-D lighting environment stably. We prove its effectiveness with experiments using a real scene under flames.

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References

  1. Basri, R., Jacobs, D.W.: Lambertian reflectance and linear subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 25(2), 218–233 (2003)

    Article  Google Scholar 

  2. Debevec, P.: Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. In: SIGGRAPH ’98: Procedings of the 25th annual conference on Computer graphics and interactive techniques, pp. 189–198 (1998)

    Google Scholar 

  3. Hara, K., Nishino, K., Ikeuchi, K.: Determining reflectance and light position from a single image without distant illumination assumption. In: IEEE International Conference on Computer Vision, vol. 2, pp. 560–567 (2003)

    Article  Google Scholar 

  4. Ihrke, I., Magnor, M.: Image-based tomographic reconstruction of flames. In: Proc. ACM/EG Symposium on Animation (SCA’04), pp. 367–375. Grenoble, France (2004)

    Google Scholar 

  5. Ikeuchi, K., Sato, K.: Determining reflectance properties of an object using range and brightness images. IEEE Trans. Pattern Anal. Mach. Intell. 13(11), 1139–1153 (1991)

    Article  Google Scholar 

  6. Lawson, C.L., Hanson, R.J.: Solving Least Squares Problems. Society for Industrial Mathematics, Philadelphia (1987)

    Google Scholar 

  7. Marschner, S.R., Greenberg, D.P.: Inverse lighting for photography. In: Fifth Color Imaging Conference, pp. 262–265 (1997)

    Google Scholar 

  8. Matsuyama, T., Wu, X., Takai, T., Nobuhara, S.: Real-Time 3D Shape Reconstruction, Dynamic 3D Mesh Deformation, and High Fidelity Visualization for 3D Video. Comput. Vis. Image Understand. 96(3), 393–434 (2004)

    Article  Google Scholar 

  9. Nillius, P., Eklundh, J.O.: Automatic estimation of the projected light source direction. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. I, pp. 1076–1083 (2001)

    Google Scholar 

  10. Pentland, A.P.: Finding the illuminant direction. J. Opt. Soc. Am. 72(4), 448–455 (1982)

    Article  Google Scholar 

  11. Phong, B.T.: Illumination for computer generated pictures. Comm. ACM 18(6), 311–317 (1975)

    Article  Google Scholar 

  12. Powell, M.W., Sarkar, S., Goldgof, D.: A simple strategy for calibrating the geometry of light sources. IEEE Trans. Pattern Anal. Mach. Intell. 23(9), 1022–1027 (2001)

    Article  Google Scholar 

  13. Ramamoorthi, R., Hanrahan, P.: A signal-processing framework for inverse rendering. In: ACM SIGGRAPH, pp. 117–128 (2001)

    Google Scholar 

  14. Sato, I., Sato, Y., Ikeuchi, K.: Acquiring a radiance distribution to superimpose virtual objects onto a real scene. IEEE Trans. Visual. Comput. Graph. 5(1), 1–12 (1999)

    Article  Google Scholar 

  15. Sato, I., Sato, Y., Ikeuchi, K.: Illumination from shadows. IEEE Trans. Pattern Anal. Mach. Intell. 25(3), 290–300 (2003)

    Article  Google Scholar 

  16. Takai, T., Maki, A., Matsuyama, T.: Self shadows and cast shadows in estimating illumination distribution. In: Fourth European Conference on Visual Media Production (2007)

    Google Scholar 

  17. Torrance, K.E., Sparrow, E.M.: Theory for off-specular reflection from roughened surfaces. J. Opt. Soc. Am. 57(9), 1105–1114 (1967)

    Article  Google Scholar 

  18. Unger, J., Wenger, A., Hawkings, T., Gardner, A., Debevec, P.: Capturing and rendering with incident light fields. In: EGRW ’03: Proceedings of the 14th Eurographics workshop on Rendering, pp. 141–149 (2003)

    Google Scholar 

  19. Wang, Y., Samaras, D.: Estimation of multiple directional illuminants from a single image. Image Vis. Comput. 26(9), 1179–1195 (2008)

    Article  Google Scholar 

  20. Yang, Y., Yuille, A.: Sources from shading. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 534–539 (1991)

    Google Scholar 

  21. Zhang, Y., Yang, Y.-H.: Multiple illuminant direction detection with application to image system. IEEE Trans. Pattern Anal. Mach. Intell. 232(8), 915–920 (2001)

    Article  Google Scholar 

  22. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

  23. Zheng, Q., Chellappa, R.: Estimation of illuminant direction, albedo, and shape from shading. IEEE Trans. Pattern Anal. Mach. Intell. 13(7), 680–702 (1991)

    Article  Google Scholar 

  24. Zhou, W., Kambhamettu, R.: Estimation of illuminant direction and intensity of multiple light sources. In: European Conference on Computer Vision, pp. 206–220 (2002)

    Google Scholar 

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Correspondence to Takeshi Takai .

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Takai, T., Iino, S., Maki, A., Matsuyama, T. (2010). 3-D Lighting Environment Estimation with Shading and Shadows. In: Ronfard, R., Taubin, G. (eds) Image and Geometry Processing for 3-D Cinematography. Geometry and Computing, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12392-4_11

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