Advertisement

Direct Bundle Estimation for Recovery of Shape, Reflectance Property and Light Position

  • Tsuyoshi Migita
  • Shinsuke Ogino
  • Takeshi Shakunaga
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5304)

Abstract

Given a set of images captured with a fixed camera while a point light source moves around an object, we can estimate the shape, reflectance property and texture of the object, as well as the positions of the light source. Our formulation is a large-scale nonlinear optimization that allows us to adjust the parameters so that the images synthesized from all of the parameters optimally fit the input images. This type of optimization, which is a variation of the bundle adjustment for structure and motion reconstruction, is often employed to refine a carefully constructed initial estimation. However, the initialization task often requires a great deal of labor, several special devices, or both. In the present paper, we describe (i) an easy method of initialization that does not require any special devices or a precise calibration and (ii) an efficient algorithm for the optimization. The efficiency of the optimization method enables us to use a simple initialization. For a set of synthesized images, the proposed method decreases the residual to zero. In addition, we show that various real objects, including toy models and human faces, can be successfully recovered.

Keywords

Input Image Preconditioned Conjugate Gradient Bundle Adjustment Photometric Stereo Point Light Source 
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.

Supplementary material

978-3-540-88690-7_31_MOESM1_ESM.wmv (5.2 mb)
Supplementary material (5,324 KB)

References

  1. 1.
    Georghiades, A.: Incorporating the torrance and sparrow model of reflectance in uncalibrated photometric stereo. In: ICCV 2003, pp. 816–823 (2003)Google Scholar
  2. 2.
    Georghiades, A.: Recovering 3-d shape and reflectance from a small number of photographs. In: Eurograpgics Symposium on Rendering, pp. 230–240 (2003)Google Scholar
  3. 3.
    Sato, Y., Ikeuchi, K.: Reflectance analysis for 3d computer graphics model generation. CVGIP 58(5), 437–451 (1996)Google Scholar
  4. 4.
    Georghiades, A., Belhumeur, P., Kriegman, D.: From few to many: Illumination cone models for face recognition under variable lighting and pose. IEEE Trans. on PAMI 23(6), 643–660 (2001)CrossRefGoogle Scholar
  5. 5.
    Lensch, H.P.A., Kautz, J., Goesele, M., Heidrich, W., Seidel, H.P.: Image-based reconstruction of spatial appearance and geometric detail. ACM Trans. on Graphics 22(3), 1–27 (2003)Google Scholar
  6. 6.
    Hertzmann, A., Seitz, S.M.: Example-based photometric stereo: Shape reconstruction with general varying brdfs. IEEE Trans. on PAMI 27(8), 1254–1264 (2005)CrossRefGoogle Scholar
  7. 7.
    Mallick, S.P., Zickler, T.E., Kriegman, D.J., Belhumeur, P.N.: Beyond lambert: Reconstructing specular surfaces using color. In: CVPR 2005, vol. 2, pp. 619–626 (2005)Google Scholar
  8. 8.
    Sato, I., Okabe, T., Yu, Q., Sato, Y.: Shape reconstruction based on similarity in radiance changes under varying illumination. In: ICCV (2007)Google Scholar
  9. 9.
    Mercier, B., Meneveaux, A., Fournier, A.: A framework for automatically recovering object shape, reflectance and light sources from calibrated images. IJCV 73(1), 77–93 (2007)CrossRefGoogle Scholar
  10. 10.
    Yu, Y., Xu, N., Ahuja, N.: Shape and view independent reflectance map from multiple views. IJCV 73(2), 123–138 (2007)CrossRefzbMATHGoogle Scholar
  11. 11.
    Goldman, D., Curless, B., Hertzmann, A.: Shape and spatially-varying brdfs from photometric stereo. In: ICCV 2005, pp. 230–240 (2005)Google Scholar
  12. 12.
    Belhumeur, P., Kriegman, D., Yuille, A.: The bas-relief ambiguity. IJCV 35(1), 33–44 (1999)CrossRefGoogle Scholar
  13. 13.
    Boivin, S., Gagalowicz, A.: Image-based rendering of diffuse, specular and glossy surfaces from a single image. SIGGRAPH, 107–116 (2001)Google Scholar
  14. 14.
    Paterson, J., Claus, D., Fitzgibbon, A.: Brdf and geometry capture from extended inhomogeneous samples using flash photography. EUROGRAPHICS 24(3), 383–391 (2005)Google Scholar
  15. 15.
    Triggs, B., McLauchlan, P.F., Hartley, R., Fitzgibbon, A.W.: Bundle adjustment — a modern synthesis. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) ICCV-WS 1999. LNCS, vol. 1883, pp. 298–375. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  16. 16.
    Marquardt, D.W.: An algorithm for least-squares estimation of nonlinear parameters. SIAM J. Appl. Math. 11, 431–441 (1963)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Shashua, A.: Geometry and photometry in 3d visual recognition, Ph. D. thesis, Dept. Brain and Cognitive Science, MIT (1992)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Tsuyoshi Migita
    • 1
  • Shinsuke Ogino
    • 1
  • Takeshi Shakunaga
    • 1
  1. 1.Department of Computer ScienceOkayama UniversityJapan

Personalised recommendations