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Estimating Photometric Properties from Image Collections

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Abstract

We address the problem of jointly estimating the scene illumination, the radiometric camera calibration and the reflectance properties of an object using a set of images from a community photo collection. The highly ill-posed nature of this problem is circumvented by using appropriate representations of illumination, an empirical model for the nonlinear function that relates image irradiance with intensity values and additional assumptions on the surface reflectance properties. Using a 3D model recovered from an unstructured set of images, we estimate the coefficients that represent the illumination for each image using a frequency framework. For each image, we also compute the corresponding camera response function. Additionally, we calculate a simple model for the reflectance properties of the 3D model. A robust non-linear optimization is proposed exploiting the high sparsity present in the problem.

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Notes

  1. Optimal in a least–squared sense.

  2. There exist particular adaptations of bundle adjustment where the scene is not rigide, for example, when working with deformable objects as the human body or animals.

  3. Images from DB1 and images used to extract the ground truth can be downloaded from http://mauriciodiazm.free.fr/MD_Prof_Webpage/Photometric_Information.html.

References

  1. Asada, N., Amano, A., Baba, M.: Photometric calibration of zoom lens systems. In: Proceedings of the 13th International Conference on Pattern Recognition, vol. 1, pp. 186–190 (1996)

    Chapter  Google Scholar 

  2. Basri, R., Jacobs, D.W.: Lambertian reflectance and linear subspaces. IEEE Trans. Pattern Anal. Mach. Intell. 5(10), 218–233 (2003)

    Article  Google Scholar 

  3. Chakrabarti, A., Scharstein, D., Zickler, T.: An empirical camera model for internet color vision. In: Proceedings of the British Machine Vision Conference (BMVC), pp. 51.1–51.11 (2009)

  4. Chang, Y.C., Reid, J.: Rgb calibration for color image analysis in machine vision. IEEE Trans. Image Process. 5(10), 1414–1422 (1996)

    Article  Google Scholar 

  5. Debevec, P., Malik, J.: Recovering high dynamic range radiance maps from photographs. In: SIGGRAPH: Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques (1997)

    Google Scholar 

  6. Diaz, M., Sturm, P.: Exploiting image collections for recovering photometric properties. In: International Conference in Computer Analysis of Images and Patterns (CAIP), vol. 2, pp. 253–261 (2011)

    Chapter  Google Scholar 

  7. Diaz, M., Sturm, P.: Radiometric calibration using photo collections. In: IEEE International Conference on Computational Photography (ICCP), pp. 1–8 (2011)

    Chapter  Google Scholar 

  8. Finlayson, G., Hordley, S., Lu, C., Drew, M.: On the removal of shadows from images. IEEE Trans. Pattern Anal. Mach. Intell. 28(1), 59–68 (2006)

    Article  Google Scholar 

  9. Furukawa, Y., Curless, B., Seitz, S.M., Szeliski, R.: Towards internet-scale multi-view stereo. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 1434–1441 (2010)

    Google Scholar 

  10. Furukawa, Y., Ponce, J.: Patch-based multi-view stereo software. See http://grail.cs.washington.edu/software/pmvs. Consulted on 01/2011

  11. Grossberg, M.D., Nayar, S.K.: What is the space of camera response functions? In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, p. 602 (2003)

    Google Scholar 

  12. Grossberg, M.D., Nayar, S.K.: Modeling the space of camera response functions. IEEE Trans. Pattern Anal. Mach. Intell. 26(10), 1272–1282 (2004)

    Article  Google Scholar 

  13. Haber, T., Fuchs, C., Bekaer, P., Seidel, H.P., Goesele, M., Lensch, H.: Relighting objects from image collections. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 627–634 (2009)

    Google Scholar 

  14. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)

    Google Scholar 

  15. Ilie, A., Welch, G.: Ensuring color consistency across multiple cameras. In: IEEE International Conference on Computer Vision (ICCV), pp. 1269–1275 (2005)

    Google Scholar 

  16. Lin, S., Gu, J., Yamazaki, S., Shum, H.Y.: Radiometric calibration from a single image. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 938–945 (2004)

    Google Scholar 

  17. Lin, S., Zhang, L.: Determining the radiometric response function from a single grayscale image. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2, pp. 66–73 (2005)

    Google Scholar 

  18. Lourakis, M., Argyros, A.: Sba: A software package for generic sparse bundle adjustment. ACM Trans. Math. Softw. 36(1), 1–30 (2009)

    Article  MathSciNet  Google Scholar 

  19. Luong, Q., Fua, P., Leclerc, Y.: The radiometry of multiple images. IEEE Trans. Pattern Anal. Mach. Intell. 24(1), 19–33 (2002)

    Article  Google Scholar 

  20. Mitsunaga, T., Nayar, S.K.: Radiometric self calibration. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 55–62 (1999)

    Google Scholar 

  21. Ng, T.T., Chang, S.F., Tsui, M.P.: Using geometry invariants for camera response function estimation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 1–8 (2007)

    Google Scholar 

  22. Ramamoorthi, R.: Modeling Illumination Variation with Spherical Harmonics. Face Processing: Advanced Modeling and Methods. Academis Press, San Diego (2005)

    Google Scholar 

  23. Ramamoorthi, R., Hanrahan, P.: A signal-processing framework for inverse rendering. In: SIGGRAPH: Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 117–128 (2001)

    Chapter  Google Scholar 

  24. Romeiro, F., Zickler, T.: Blind reflectometry. In: European Conference on Computer Vision (ECCV) (2010)

  25. Snavely, N., Seitz, S.M., Szeliski, R.: Photo tourism: exploring photo collections in 3d. In: (ACM) Transactions on Graphics, pp. 835–846 (2006)

    Google Scholar 

  26. Snavely, N., Seitz, S.M., Szeliski, R.: Modeling the world from internet photo collections. Int. J. Comput. Vis. 80(2), 189–210 (2008)

    Article  Google Scholar 

  27. Takamatsu, J., Matsushita, Y., Ikeuchi, K.: Estimating camera response functions using probabilistic intensity similarity. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 33–41 (2008)

    Google Scholar 

  28. Yu, Y., Debevec, P., Malik, J., Hawkins, T.: Inverse global illumination: recovering reflectance models of real scenes from photographs. In: SIGGRAPH: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques (1999)

    Google Scholar 

  29. Zhang, Z.: Parameter estimation techniques: a tutorial with application to conic fitting. Image Vis. Comput. 15, 59–76 (1997)

    Article  Google Scholar 

  30. Zickler, T.: Principles of appearance acquisition and representation. In: Foundations and Trends in Computer Graphics and Vision, pp. 1–119 (2009)

  31. Seitz, S.M., Curless, B., Diebel, J., Scharstein, D.: A comparison and evaluation of multi–view stereo reconstruction algorithms. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. 154–162 (2006)

    Google Scholar 

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Authors and Affiliations

  1. INRIA Grenoble Rhône-Alpes—Lab. LJK, 655 Avenue de l’Europe, Montbonnot St. Martin, France

    Mauricio Diaz & Peter Sturm

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  1. Mauricio Diaz
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  2. Peter Sturm
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Correspondence to Mauricio Diaz.

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Diaz, M., Sturm, P. Estimating Photometric Properties from Image Collections. J Math Imaging Vis 47, 93–107 (2013). https://doi.org/10.1007/s10851-013-0442-7

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