Skip to main content
SpringerLink
Log in

When Shadows Become Interreflections

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

Shadows and interreflections are present in all real scenes and provide a rich set of photometric cues for vision. In this paper, we show how shadows and interreflections are intrinsically related. Shadows tend to occur in those parts of a scene in which interreflections have the largest gain. We provide several basic results concerning this relationship in terms of the interreflection modes of a scene. We show that for a given scene, the interreflection mode having the largest gain is a physically realizable radiance function. We derive bounds on the gain of this mode and discuss how this mode is related to shadows. We analyze how well an n-bounce model of interreflections approximates an infinite-bounce model and how shadows affect this approximation. Finally, we introduce a novel method for inferring surface color in a uni-chromatic scene. The method is based on the relative contrast of the scene in different color channels.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Anstis, S. 1992. Visual adaptation to a negative brightness reversed world: Some preliminary observations. Neural Networks for Vision and Image Processing. The MIT Press.

  • Baum, D.R., Rushmeier, H.E., and Winget, J.M. 1989. Improving radiosity solutions through the use of analytically determined form factors. In Proc. SIGGRAPH.

  • Belhumeur, P.N., Kriegman, D.J., and Yuille, A. 1997. The bas-relief ambiguity. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, San Juan, PR.

  • Foley, J.D., van Dam, A., Feiner, S.K., and Hughes, J.F. 1990. Computer Graphics: Principles and Practice. Addison-Wesley: Reading, MA, 2nd edition.

    Google Scholar 

  • Forsyth, D. and Zisserman, A. 1991. Reflections on shading. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13:671–679.

    Google Scholar 

  • Funt, B.V. and Drew, M.S. 1993. Color space analysis of mutual illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(12):1319–1326.

    Google Scholar 

  • Funt, B.V., Drew, M.S., and Ho, J. 1991. Color constancy from mutual reflection. International Journal of Computer Vision, 6(1):5–24.

    Google Scholar 

  • Gershon, R., Jepson, A.D., and Tsotsos, J.K. 1990. Ambient illumination and the determination of material changes. Journal of the Optical Society of America, 7(10):2041–2047.

    Google Scholar 

  • Gilchrist, A. and Jacobsen, A. 1984. Perception of lightness and illumination in a world of one reflectance. Perception, 13:5–19.

    Google Scholar 

  • Gilchrist, A.L. and Ramachandran, V.S. 1993. Red rooms in white light look different than white rooms in red light. In Invest. Oph. and Vis. Sci. (ARVO abstract).

  • Haddon, J. and Forsyth, D. 1998. Shading primitives: Finding folds and shallow grooves. In Proceedings of the Sixth International Conference on Computer Vision, Bombay, India.

  • Kersten, D.K. and Hurlbert, A.C. 1996. Discounting the color of mutual illumination: A 3-d-shape-induced color phenomenon. In Invest. Oph. and Vis. Sci. (abstract).

  • Kœnderink, J.J. and van Doorn, A.J. 1983. Geometrical modes as a general method to treat diffuse interreflections in radiometry. J. Opt. Soc. Am., 73(6):843–850.

    Google Scholar 

  • Langer, M.S. and Zucker, S.W. 1994. Shape from shading on a cloudy day. Journal of the Optical Society of America A, 11(2):467–478.

    Google Scholar 

  • Moon, P. 1940. On interreflections. Journal of the Optical Society of America, 30:195–205.

    Google Scholar 

  • Moon, P.H. and Spencer, D.E. 1981. The Photic Field. MIT Press: Cambridge, MA.

    Google Scholar 

  • Nayar, S.K. and Gong, Y.G. 1992. Colored interreflections and shape recovery. In Image Understanding Workshop, San Diego, DARPA, pp. 333–343.

    Google Scholar 

  • Nayar, S.K., Ikeuchi, K., and Kanade, T. 1991. Shape from interreflections. International Journal of Computer Vision, 6:173–195.

    Google Scholar 

  • Oren, M. and Nayar, S.K. 1994. Seeing beyond lambert's law. In ECCV' 94. Lecture Notes in Computer Science 801, Springer-Verlag, pp. 269–280.

  • Rubin, J.M. and Richards, W.A. 1982. Color vision and image intensities: When are the changes material? Biological Cybernetics, (45):215–226.

    Google Scholar 

  • Shafer, S.A. 1985. Shadows and Silhouettes in Computer Vision. Kluwer Academic Publishers.

  • Siegel, R. and Howell, J.R. 1981. Thermal Radiation Heat Transfer. Hemisphere Publ. Corp.

  • Spencer, D.E. and Sanborn, S.E. 1961. Interreflections and color. Journal of the Franklin Institute, 252:413–426.

    Google Scholar 

  • Waltz, D. 1975. Understanding line drawings of scenes with shadows. The Psychology of Computer Vision, McGraw-Hill: New York, pp. 19–91.

    Google Scholar 

Download references

Authors
  1. M.S. Langer
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Langer, M. When Shadows Become Interreflections. International Journal of Computer Vision 34, 193–204 (1999). https://doi.org/10.1023/A:1008131719047

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008131719047

Search

Navigation