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Surface Reconstruction Using Polarization and Photometric Stereo

  • Gary A. Atkinson
  • Edwin R. Hancock
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

This paper presents a novel shape recovery technique that combines photometric stereo with polarization information. First, a set of ambiguous surface normals are estimated from polarization data. This is achieved using Fresnel theory to interpret the polarization patterns of light reflected from dielectric surfaces. The process is repeated using three different known light source positions. Photometric stereo is then used to disambiguate the surface normals. The relative pixel brightnesses for the different light source positions reveal the correct surface orientations. Finally, the resulting unambiguous surface normal estimates are integrated to recover a depth map. The technique is tested on various objects of different materials. The paper also demonstrates how the depth estimates can be enhanced by applying methods suggested in earlier work.

Keywords

Singular Value Decomposition Surface Normal Zenith Angle Azimuth Angle Shape Recovery 
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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References

  1. 1.
    Atkinson, G.A., Hancock, E.R.: Shape estimation using polarization and shading from two views. IEEE Trans. Patt. Anal. Mach. Intell. (to appear)Google Scholar
  2. 2.
    Atkinson, G.A., Hancock, E.R.: Recovery of surface orientation from diffuse polarization. IEEE Trans. Im. Proc. 15, 1653–1664 (2006)CrossRefGoogle Scholar
  3. 3.
    Drbohlav, O., Šára, R.: Unambiguous determination of shape from photometric stereo with unknown light sources. In: Proc. ICCV, pp. 581–586 (2001)Google Scholar
  4. 4.
    Frankot, R.T., Chellappa, R.: A method for enforcing integrability in shape from shading algorithms. IEEE Trans. Patt. Anal. Mach. Intell. 10, 439–451 (1988)zbMATHCrossRefGoogle Scholar
  5. 5.
    Hecht, E.: Optics, 3rd edn. Addison Wesley Longman, London, UK (1998)Google Scholar
  6. 6.
    Miyazaki, D., Kagesawa, M., Ikeuchi, K.: Transparent surface modelling from a pair of polarization images. IEEE Trans. Patt. Anal. Mach. Intell. 26, 73–82 (2004)CrossRefGoogle Scholar
  7. 7.
    Miyazaki, D., Tan, R.T., Hara, K., Ikeuchi, K.: Polarization-based inverse rendering from a single view. In: Proc. ICCV, vol. 2, pp. 982–987 (2003)Google Scholar
  8. 8.
    Rahmann, S., Canterakis, N.: Reconstruction of specular surfaces using polarization imaging. In: Proc. CVPR, pp. 149–155 (2001)Google Scholar
  9. 9.
    Wolff, L.B., Boult, T.E.: Constraining object features using a polarisation reflectance model. IEEE Trans. Patt. Anal. Mach. Intell. 13, 635–657 (1991)CrossRefGoogle Scholar
  10. 10.
    Woodham, R.J.: Photometric method for determining surface orientation from multiple images. Optical Engineering 19, 139–144 (1980)Google Scholar
  11. 11.
    Yuille, A.L., Snow, D., Epstein, R., Belhumeur, P.: Determining generative models for objects under varying illumination: Shape and albedo from multiple images using SVD and integrability. Intl. J. Comp. Vis. 35, 203–222 (1999)CrossRefGoogle Scholar
  12. 12.
    Zhang, R., Tsai, P.S., Cryer, J.E., Shah, M.: Shape from shading: A survey. IEEE Trans. Patt. Anal. Mach. Intell. 21, 690–706 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Gary A. Atkinson
    • 1
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer Science, University of York, York, YO1 5DDUK

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