Advertisement

The Visual Computer

, Volume 29, Issue 6–8, pp 825–835 | Cite as

Three-dimensional reconstruction using multiresolution photoclinometry by deformation

  • Claire Capanna
  • Gilles Gesquière
  • Laurent Jorda
  • Philippe Lamy
  • Didier Vibert
Original Article

Abstract

We present a new photoclinometric reconstruction method based on the deformation of a 3D mesh. The optimization process of our method relies on a maximum-likelihood estimation with a density function measuring discrepancies between observed images and the corresponding synthetic images calculated from the progressively deformed 3D mesh. An input mesh is necessary and can be obtained from other methods or created by implementing a multiresolution scheme. We present a 3D shape model of an asteroid obtained by this method and compare it with the models obtained with two high-resolution 3D reconstruction techniques, stereophotogrammetry, and stereophotoclinometry.

Keywords

Photoclinometry 3D Reconstruction Mesh deformation Optimization Multiresolution 

References

  1. 1.
    Botsch, M., et al.: Geometric Modeling Based on Polygonal Meshes. ACM, New York (2007) Google Scholar
  2. 2.
    Briggs, W., McCormick, S.: Multigrid Methods. Frontiers in Applied Mathematics. SIAM, Philadelphia (1987) zbMATHGoogle Scholar
  3. 3.
    Byrd, R., Nocedal, J., Schnabel, R.: Representation of quasi-Newton matrices and their use in limited memory methods. Math. Program. 63(4), 129–156 (1994) MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Gaskell, R., et al.: Characterizing and navigating small bodies with imaging data. Meteorit. Planet. Sci. 43, 1049–1061 (2008) CrossRefGoogle Scholar
  5. 5.
    Giese, B., Oberst, J., Kirk, R., Zeitler, W.: The topography of asteroid ida: a comparison between photogrammetric and two-dimensional photoclinometric image analysis. Int. Arch. Photogramm. Remote Sens. XXXI, 245–250 (1996) Google Scholar
  6. 6.
    Gill, P.E., Murray, W., Wright, M.H.: Practical Optimization. Academic Press, San Diego (1981) zbMATHGoogle Scholar
  7. 7.
    Girardeau-Montaut, D., et al.: Change detection on points cloud data acquired with a ground laser scanner. In: ISPRS Workshop Laser Scanning III/3, pp. 30–35 (2005) Google Scholar
  8. 8.
    Gwinner, K., et al.: Derivation and validation of highresolution digital terrain models from mars express HRSC-data. Photogramm. Eng. Remote Sens. Sens, 1127–1142 (2007) Google Scholar
  9. 9.
    Jorda, L., Spjuth, S., Keller, H.U., Lamy, P., Llebaria, A.: OASIS: a simulator to prepare and interpret remote imaging of solar system bodies. Proc. SPIE 7533, 12 (2010) Google Scholar
  10. 10.
    Lamy, P.L., Faury, G., Jorda, L., Kaasalainen, M., Hviid, S.F.: Multi-color, rotationally resolved photometry of asteroid 21 Lutetia from OSIRIS/Rosetta observations. Astron. Astrophys. 521, 19 (2010) CrossRefGoogle Scholar
  11. 11.
    Lohse, V., Heipke, C., Kirk, R.L.: Derivation of planetary topography using multi-image shape-from-shading. Planet. Space Sci. 54, 661–674 (2006) CrossRefGoogle Scholar
  12. 12.
    Loop, C.T.: Smooth Subdivision Surfaces Based on Triangles. M.S. thesis, University of Utah (1987) Google Scholar
  13. 13.
    Morales, J.L., Nocedal, J.: Remark on “Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization”. ACM Trans. Math. Softw. 38(1), 1–4 (2011) MathSciNetCrossRefGoogle Scholar
  14. 14.
    More, J.: The Levenberg–Marquardt algorithm: implementation and theory. In: Numerical Analysis, vol. 630, pp. 105–116 (1978) CrossRefGoogle Scholar
  15. 15.
    Peleg, S., Ron, G.: Nonlinear multiresolution: a shape-from-shading example. IEEE Trans. Pattern Anal. Mach. Intell. 12(12), 1206–1210 (1990) CrossRefGoogle Scholar
  16. 16.
    Prados, E., Faugeras, O., Camilli, F.: Shape from shading: a well-posed problem? Research report 5297, Institut National de Recherche en Informatique et en Automatique, Sophia Antipolis, France (2004) Google Scholar
  17. 17.
    Preusker, F., et al.: The northern hemisphere of asteroid 21 Lutetia topography and orthoimages from Rosetta OSIRIS NAC image data. Planet. Space Sci. 66, 54–63 (2012) CrossRefGoogle Scholar
  18. 18.
    Rindfleisch, T.: Photometric method for lunar topography. Photogramm. Eng. 32(2), 262–277 (1966) Google Scholar
  19. 19.
    Samavati, F., Pakdel, H., Smith, C., Prusinkiewicz, P.: Reverse Loop Subdivision. Technical report 2003-730-33, University of Calgary (2003) Google Scholar
  20. 20.
    Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int. J. Comput. Vis. 47, 7–42 (2001) CrossRefGoogle Scholar
  21. 21.
    Seitz, S.M., Curless, B., Diebel, J., Scharstein, D., Szeliski, R.: A comparison and evaluation of multi-view stereo reconstruction algorithms. In: Proc. CVPR, pp. 519–528 (2006) Google Scholar
  22. 22.
    Sierks, H., et al.: Images of asteroid 21 Lutetia: a Remnant planetesimal from the Early Solar System. Science 334, 487–490 (2011) CrossRefGoogle Scholar
  23. 23.
    Szalay, A., et al.: Indexing the sphere with the hierarchical triangular mesh. Technical report MSR-TR-2005-123, Microsoft Research (2005) Google Scholar
  24. 24.
    Tarini, M., Callieri, M., Montani, C., Rocchini, C.: Marching intersections: an efficient approach to shape-from-silhouette. In: Conference on Vision, Modeling, and Visualization Proceedings, pp. 255–262 (2002) Google Scholar
  25. 25.
    Terzopoulos, D.: Efficient Multiresolution Algorithms for Computing Lightness, Shape-from-Shading, and Optical Flow, AAAI-84 Proceedings (1984) Google Scholar
  26. 26.
    Wu, C., Wilburn, B., Matsushita, Y., Theobalt, C.: High-quality shape from multi-view stereo and shading under general illumination. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 969–976 (2011) Google Scholar
  27. 27.
    Zhang, R., Tsai, P., Edwin, J., Shah, M.: Shape from shading: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 21(8), 690–706 (1999) CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Claire Capanna
    • 1
    • 2
  • Gilles Gesquière
    • 3
  • Laurent Jorda
    • 2
  • Philippe Lamy
    • 2
  • Didier Vibert
    • 2
  1. 1.Aix Marseille Université, CNRSLSIS (Laboratoire des Sciences de l’Information et des Systèmes) UMR 7296MarseilleFrance
  2. 2.Aix Marseille Université, CNRSLAM (Laboratoire d’Astrophysique de Marseille) UMR 7326MarseilleFrance
  3. 3.Université Lumière, CNRSLaboratoire LIRIS (Laboratoire d’InfoRmatique en Image et Systèmes d’information) UMR 5205LyonFrance

Personalised recommendations