Shape from Single Stripe Pattern Illumination

  • S. Winkelbach
  • F. M. Wahl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2449)


This paper presents a strategy for rapid reconstruction of surfaces in 3d which only uses a single camera shot of an object illuminated with a simple stripe pattern. With this respect, it is a meaningful extension of our ‘shape from 2d edge gradient’ method introduced earlier. The reconstruction is based on determining stripe directions and stripe widths in the camera image in order to estimate surface orientation. I.e., this method does not use triangulation for range data acquisition, but rather computes surface normals. These normals can be 2d integrated and thus yield the surface coordinates; in addition they can be used to compute robust 3d features of free-form surfaces for object recognition, pose estimation, etc. The method is straightforward and very efficient by processing only one image and using only simple image processing operations.


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  1. 1.
    D. C. Marr, T. Poggio: A computational theory of human stereo vision, Proc. Roy. Soc. London 204, 1979Google Scholar
  2. 2.
    T. Ueda, M. Matsuki: Time Sequential Coding for Three-Dimensional Measurement and Its Implementation, Denshi-Tsushin-Gakkai-Ronbunshi, 1981Google Scholar
  3. 3.
    M. Oshima, Y. Shirai: Object recognition using three dimensional information, IEEE Transact. on PAMI, vol. 5, July 1983Google Scholar
  4. 4.
    K. L. Boyer and A. C. Kak: Color-Encoded Structured Light for Rapid Active Ranging, IEEE Transact. on PAMI, vol. 9, no. 1, Januar 1987Google Scholar
  5. 5.
    F. M. Wahl: A Coded Light Approach for 3-Dimensional (3D) Vision, IBM Research Report RZ 1452, 1984Google Scholar
  6. 6.
    M. Maruyama, S. Abe: Range Sensing by Projection Multiple Slits with Random Cuts, IEEE PAMI 15(6), pp. 647–650, 1993.Google Scholar
  7. 7.
    P. Vuylsteke, A. Oosterlinck, Range Image Acquisition with a Single Binary-Encoded Light Pattern, IEEE Transact. on PAMI, vol. 12, no. 2, 1990.Google Scholar
  8. 8.
    J.J. Gibson, The Perception of the Visual World, MA: Reverside Press, Cambridge, 1950Google Scholar
  9. 9.
    J.R. Kender, Shape from texture, Proc. DARPA IU Workshop, November 1978Google Scholar
  10. 10.
    B. K. P. Horn and M. J. Brooks: Shape from Shading, M.I.T., Cambridge, 1989Google Scholar
  11. 11.
    G. Healey, T.O. Binford: Local Shape from Specularity, Proc. ICCV, London, June 1987Google Scholar
  12. 12.
    S. Winkelbach, F.M. Wahl: Shape from 2D Edge Gradients, Pattern Recognition, Lecture Notes in Computer Science 2191, Springer, 2001Google Scholar
  13. 13.
    M. Asada, H. Ichikawa, S. Tjuji: Determining of Surface Properties by Projecting a Stripe Pattern, IEEE Proc. of ICPR’86, 1986Google Scholar
  14. 14.
    M. Asada, H. Ichikawa, S. Tsuji: Determining Surface Orientation by Projecting a Stripe Pattern, IEEE Transact. on PAMI, vol. 10, no. 5, September 1988Google Scholar
  15. 15.
    M. Proesmans, L. Van Gool and A. Oosterlinck: One-Shot Active Shape Acquisition, IEEE Proc. of ICPR’96, 1996Google Scholar
  16. 16.
    Robert T. Frankot, R. Chellappa: A Method for Enforcing Integrability in Shape from Shading Algorithms, IEEE Transact. on PAMI, vol. 10, no. 4, July 1988Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • S. Winkelbach
    • 1
  • F. M. Wahl
    • 1
  1. 1.Institute for Robotics and Process ControlTechnical University of BraunschweigBraunschweigGermany

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