3D Shape Recovery by the Use of Single Image Plus Simple Pattern Illumination

  • Zhan Song
  • Ronald Chung
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4841)


This paper presents a method of surface orientation and in turn shape recovery from a single image captured under projection of a simple checker-board pattern. The essences of the method include that only one image is required, that accurate correspondence establishment between the image and the projected pattern is not necessary, that the determination of 3D is much less sensitive to imaging noise and illumination condition than intensity-based methods like shape from shading. The method relies upon the fact that surface orientations at the grid points are only decided by image tangents in the image data. Experiments on planar, spherical, and ribbon-like surfaces show that, with accurate calibration of the projector-and-camera system through a mechanism we proposed earlier, 3D shape can be recovered with ease and precision both much better than before.


Object Surface Relative Depth Surface Orientation Parallel Projection Face Orientation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Taylor, C.J.: Surface Reconstruction from Feature Based Stereo. In: 9th IEEE International Conference on Computer Vision, pp. 184–190 (2003)Google Scholar
  2. 2.
    Salvi, J., Pages, J., Batlle, J.: Pattern Codification Strategies in Structured Light Systems. Pattern Recognition 37(4), 827–849 (2004)zbMATHCrossRefGoogle Scholar
  3. 3.
    Kawasaki, H., Furukawa, R.: 3D Acquisition System using Uncalibrated Line-Laser Projector. In: 18th International Conference on Pattern Recognition, vol. 1, pp. 975–979 (2006)Google Scholar
  4. 4.
    Garding, J.: Direct Estimation of Shape from Texture. IEEE Trans. on PAMI 15, 1202–1208 (1993)Google Scholar
  5. 5.
    Zhang, R., Tsai, P., Cryer, J.E., Shah, M.: Shape from Shading: A Survey. IEEE Trans on. PAMI 21(8), 690–705 (1999)Google Scholar
  6. 6.
    Healey, G., Binford, T.O.: Local Shape from Specularity. In: 1st ICCV, pp. 151–160 (1987)Google Scholar
  7. 7.
    Bronstein, A.M., Bronstein, M.M., Kimmel, R.: Three-Dimensional Face Recognition. Computer Vision 64(1), 5–30 (2005)CrossRefGoogle Scholar
  8. 8.
    Brooks, M.J., Chojnacki, W.: Direct Computation of Shape from Shading. In: 12th International Conference on Pattern Recognition, pp. 114–119 (1994)Google Scholar
  9. 9.
    Lange, H.: Advances in the Cooperation of Shape from Shading and Stereo Vision. Second International Conference on 3-D Imaging and Modeling, 46–58 (1999)Google Scholar
  10. 10.
    Woodham, R.J.: Photometric Stereo: A Reflectance Map Technique for Determining Surface Orientation from Image Intensity. In: 22nd Int. Symp. SPIE, vol. 155, pp. 136–143 (1978)Google Scholar
  11. 11.
    Shrikhande, N., Stockman, G.: Surface Orientation from a Projected Grid. IEEE Trans. on PAMI 2(6) (1989)Google Scholar
  12. 12.
    Horn, B.K.P., Brooks, M.J.: The Variational Approach to Shape from Shading. Computer Vision Graphics Image Processing 33, 174–208 (1986)CrossRefGoogle Scholar
  13. 13.
    Sugihara, K., Okazaki, K., Kaihua, F., Sugie, N.: Regular Pattern Projection for Surface Measurement. In: 2nd International Symp. Robotics Research, pp. 17–24 (1984)Google Scholar
  14. 14.
    Winkelbach, S., Wahl, F.M.: Shape from 2D Edge Gradients. In: Radig, B., Florczyk, S. (eds.) Pattern Recognition. LNCS, vol. 2191, pp. 377–384. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  15. 15.
    Winkelbach, S., Wahl, F.M.: Shape from Single Stripe Pattern Illumination. In: Van Gool, L. (ed.) Pattern Recognition. LNCS, vol. 2449, pp. 240–247. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  16. 16.
    Asada, M., Ichikawa, H., Tsuji, S.: Determining Surface Orientation by Projecting a Stripe Pattern. IEEE Trans. on PAMI 10(5), 749–754 (1988)Google Scholar
  17. 17.
    Robert, T., Frankot, R.: A Method for Enforcing Integrability in Shape from Shading Algorithms. IEEE Trans. on PAMI 10(4) (1988)Google Scholar
  18. 18.
    Song, Z., Chung, R., Yeung, S.W.-L.: An Accurate Camera-Projector System Calibration by the use of an LCD Panel. In: Proceedings of the 2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, pp. 164–170 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Zhan Song
    • 1
  • Ronald Chung
    • 1
  1. 1.Department of Mechanical & Automation Engineering, The Chinese University of Hong Kong, Hong KongChina

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