Skip to main content
Log in

The Bas-Relief Ambiguity

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

Abstract

When an unknown object with Lambertian reflectance is viewed orthographically, there is an implicit ambiguity in determining its 3-d structure: we show that the object's visible surface f(x, y) is indistinguishable from a “generalized bas-relief” transformation of the object's geometry, \( {\bar f} \) (x, y) = λf(x, y) + μx + νy, and a corresponding transformation on the object's albedo. For each image of the object illuminated by an arbitrary number of distant light sources, there exists an identical image of the transformed object illuminated by similarly transformed light sources. This result holds both for the illuminated regions of the object as well as those in cast and attached shadows. Furthermore, neither small motion of the object, nor of the viewer will resolve the ambiguity in determining the flattening (or scaling) λ of the object's surface. Implications of this ambiguity on structure recovery and shape representation are discussed.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Artin, E. 1957. Geometric Algebra. Interscience Publishers, Inc.: New York.

    Google Scholar 

  • Baxandall, M. 1995. Shadows and Enlightenment. Yale University Press: New Haven.

    Google Scholar 

  • Belhumeur, P.N. and Kriegman, D.J. 1996. What is the set of images of an object under all possible lighting conditions? In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 270–277.

  • Belhumeur, P.N. and Kriegman, D.J. 1998. What is the set of images of an object under all possible lighting conditions? Int. J. Computer Vision, 28:245–260.

    Google Scholar 

  • Epstein, R., Yuille, A., and Belhumeur, P.N. 1996. Learning and recognizing objects using illumination subspaces. In Proc. of the Int. Workshop on Object Representation for Computer Vision.

  • Fan, J. and Wolff, L. 1997. Surface curvature and shape reconstruction from unknown multiple illumination and integrability. Computer Vision and Image Understanding, 65(2):347–359.

    Google Scholar 

  • Faugeras, O. 1995. Stratification of 3-D vision: Projective, affine, and metric representations. J. Opt. Soc. Am. A, 12(7):465–484.

    Google Scholar 

  • Fermuller, C. and Aloimonos, Y. 1996. Ordinal representations of visual space. In Proc. Image Understanding Workshop, pp. 897–904.

  • Georghiades, A., Kriegman, D., and Belhumeur, P. 1998. Illumination cones for recognition under variable lighting: Faces. In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 52–59.

  • Hayakawa, H. 1994. Photometric stereo under a light-source with arbitrary motion. JOSA-A, 11(11):3079–3089.

    Google Scholar 

  • Horn, B. 1986. Computer Vision. MIT Press, Cambridge, Mass.

    Google Scholar 

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

    Google Scholar 

  • Huang, T.S. and Lee, C.H. 1989. Motion and structure from orthographic projection. IEEE Trans. Pattern Anal. Mach. Intelligence, 11(5):536–540.

    Google Scholar 

  • Jacobs, D. 1997. Linear fitting with missing data: Applications to structure from motion and characterizing intensity images. In Proc. IEEE Conf. on Comp. Vision and Patt. Recog.

  • Kemp, M. (Ed.) 1989. Leonardo On Painting. Yale University Press: New Haven.

    Google Scholar 

  • Kemp, M. 1990. The Science of Art: Optical Themes in Western Art from Brunelleschi to Seurat. Yale University Press: New Haven.

    Google Scholar 

  • Koenderink, J. and Van Doorn, A. 1991. Affine structure from motion. JOSA-A, 8(2):377–385.

    Google Scholar 

  • Koenderink, J. and van Doorn, A. 1997. The generic bilinear calibration estimation problem. Int. J. Computer Vision, 23(3):217–234.

    Google Scholar 

  • Koenderink, J.J., Van Doorn, A.J., and Christon, C. 1996. Shape constancy in pictorial relief. In Object Representation in Computer Vision II, J. Ponce, A. Zisserman, and M. Hebert, (Eds.), pp. 151–164. Springer.

  • Lambert, J. 1760. Photometria Sive de Mensura et Gradibus Luminus, Colorum et Umbrae. Eberhard Klett.

  • Langer, M. and Zucker, S. 1997. What is a light source? In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 172–178.

  • Longuet-Higgins, H. 1981. A computer algorithm for reconstructing a scene from two projections. Nature, 293:133–135.

    Google Scholar 

  • Oliensis, J. 1991. Uniqueness in shape from shading. Int. J. Computer Vision, 6(2):75–104.

    Google Scholar 

  • Oliensis, J. 1996. Structure from linear or planar motions. In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 335–342.

  • Roach, J. and Aggarwal, K.J. 1979. Computer tracking of objects from a sequence of images. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1(2):127–135.

    Google Scholar 

  • Rosenholtz, R. and Koenderink, J. 1996. Affine structure and photometry. In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 790–795.

  • Shapiro, L., Zisserman, A., and Brady, M. 1995. 3D motion recovery via affine epipolar geometry. Int. J. Computer Vision, 16(2):147–182.

    Google Scholar 

  • Shashua, A. 1992. Geometry and Photometry in 3D Visual Recognition. Ph.D. Thesis, MIT.

  • Silver, W. 1980. Determining Shape and Reflectance Using Multiple Images. Ph.D. Thesis, MIT, Cambridge, MA.

    Google Scholar 

  • Szeliski, R. and Kang, S. 1996. Shape ambiguities in structure from motion. In European Conf. on Computer Vision, vol. I, pp. 709–721.

    Google Scholar 

  • Ullman, S. and Basri, R. 1991. Recognition by a linear combination of models. IEEE Trans. Pattern Anal. Mach. Intelligence, 13:992–1006.

    Google Scholar 

  • von Helmholtz, H. 1910. Handbuch der Physiologischen Optik. Verlag von Leopoled Voss, Hamburg, Germany.

    Google Scholar 

  • Waxman, A. and Ullman, S. 1985. Surface structure and three-dimensional motion from image flow kinematics. Int. J. Robotics Research, 4:72–92.

    Google Scholar 

  • Woodham, R. 1981. Analysing images of curved surfaces. Artificial Intelligence, 17:117–140.

    Google Scholar 

  • Yuille, A. and Snow, D. 1997. Shape and albedo from multiple images using integrability. In Proc. IEEE Conf. on Comp. Vision and Patt. Recog., pp. 158–164.

Download references

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Belhumeur, P.N., Kriegman, D.J. & Yuille, A.L. The Bas-Relief Ambiguity. International Journal of Computer Vision 35, 33–44 (1999). https://doi.org/10.1023/A:1008154927611

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008154927611

Navigation