Shape from Fluorescence

  • Tali Treibitz
  • Zak Murez
  • B. Greg Mitchell
  • David Kriegman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7578)


Beyond day glow highlighters and psychedelic black light posters, it has been estimated that fluorescence is a property exhibited by 20% of objects. When a fluorescent material is illuminated with a short wavelength light, it re-emits light at a longer wavelength isotropically in a similar manner as a Lambertian surface reflects light. This hitherto neglected property opens the doors to using fluorescence to reconstruct 3D shape with some of the same techniques as for Lambertian surfaces – even when the surface’s reflectance is highly non-Lambertian. Thus, performing reconstruction using fluorescence has advantages over purely Lambertian surfaces. Single image shape-from-shading and calibrated Lambertian photometric stereo can be applied to fluorescence images to reveal 3D shape. When performing uncalibrated photometric stereo, both fluorescence and reflectance can be used to recover Euclidean shape and resolve the generalized bas relief ambiguity. Finally for objects that fluoresce in wavelengths distinct from their reflectance (such as plants and vegetables), reconstructions do not suffer from problems due to inter-reflections. We validate these claims through experiments.


3D Reconstruction Photometric Stereo Shape from Shading Fluorescence Subsurface Scattering 


  1. 1.
    Barnard, K.: Color constancy with fluorescent surfaces. In: Proc. IS&T/SID Seventh Color Imaging Conference: Color Science, Systems and Applications (1999)Google Scholar
  2. 2.
    Woodham, R.: Photometric method for determining surface orientation from multiple images. Opt. Eng. 19, 139–144 (1980)Google Scholar
  3. 3.
    Silver, W.M.: Determining shape and reflectance using multiple images. Master’s thesis, Massachusetts Institute of Technology (1980)Google Scholar
  4. 4.
    Guilbault, G.: Practical fluorescence, vol. 3. CRC (1990)Google Scholar
  5. 5.
    Ihrke, I., Goidluecke, B., Magnor, M.: Reconstructing the geometry of flowing water. In: Proc. IEEE ICCV (2005)Google Scholar
  6. 6.
    Hullin, M., Fuchs, M., Ihrke, I., Seidel, H., Lensch, H.: Fluorescent immersion range scanning. ACM TOG 27 (2008)Google Scholar
  7. 7.
    Glassner, A.: Principles of Digital Image Synthesis, ch. 17. Morgan Kaufmann Publishers (1995)Google Scholar
  8. 8.
    Sato, I., Okabe, T., Sato, Y.: Bispectral photometric stereo based on fluorescence. Trans. IEEE CVPR (2012)Google Scholar
  9. 9.
    Szeliski, R.: Computer vision: Algorithms and applications. Springer (2010)Google Scholar
  10. 10.
    Horn, B.: Robot vision, ch. 10. The MIT Press (1986)Google Scholar
  11. 11.
    Oren, M., Nayar, S.: Generalization of the lambertian model and implications for machine vision. IJCV 14, 227–251 (1995)CrossRefGoogle Scholar
  12. 12.
    Phong, B.: Illumination for computer generated pictures. Communications of the ACM 18, 311–317 (1975)CrossRefGoogle Scholar
  13. 13.
    Cook, R., Torrance, K.: A reflectance model for computer graphics. ACM TOG 1, 7–24 (1982)Google Scholar
  14. 14.
    Ashikhmin, M., Shirley, P.: An anisotropic phong BRDF model. J. of Graphics Tools 5, 25–32 (2000)CrossRefGoogle Scholar
  15. 15.
    Treibitz, T., Neal, B.P., Roberts, P., Kline, D.I., Beijbom, O., Belongie, S., Mitchell, B.G., Jaffe, J., Kriegman, D.: Wide field of view full spectrum fluorescence imaging for coral ecology. In: International Coral Reef Symposium (2012)Google Scholar
  16. 16.
    Zhang, C., Sato, I.: Separating reflective and fluorescent components of an image. In: Proc. IEEE CVPR (2011)Google Scholar
  17. 17.
    Alterman, M., Schechner, Y., Weiss, A.: Multiplexed fluorescence unmixing. In: Proc. IEEE ICCP (2010)Google Scholar
  18. 18.
    Wilkie, A., Weidlich, A., Larboulette, C., Purgathofer, W.: A reflectance model for diffuse fluorescent surfaces. In: Proc. Int. Conf. Comp. graphics & interactive techniques in Australasia and Southeast Asia, pp. 321–331 (2006)Google Scholar
  19. 19.
    Hullin, M., Hanika, J., Ajdin, B., Seidel, H., Kautz, J., Lensch, H.: Acquisition and analysis of bispectral bidirectional reflectance and reradiation distribution functions. ACM TOG 29 (2010)Google Scholar
  20. 20.
    Kratohvil, J., Lee, M., Kerker, M.: Angular distribution of fluorescence from small particles. Applied Optics 17 (1978)Google Scholar
  21. 21.
    Gordon, H., Voss, K., Kilpatrick, K.: Angular distribution of fluorescence from phytoplankton. Limnology and Oceanography, 1582–1586 (1993)Google Scholar
  22. 22.
    Collins, D., Kiefer, D., Soohoo, J., Stuart McDermid, I.: The role of reabsorption in the spectral distribution of phytoplankton fluorescence emission. Deep Sea Research Part A. Oceanographic Research Papers 32, 983–1003 (1985)CrossRefGoogle Scholar
  23. 23.
    Zhang, R., Tsai, P., Cryer, J., Shah, M.: Shape-from-shading: a survey. IEEE Trans. PAMI 21, 690–706 (1999)CrossRefGoogle Scholar
  24. 24.
    Durou, J., Falcone, M., Sagona, M.: Numerical methods for shape-from-shading: A new survey with benchmarks. Computer Vision and Image Understanding 109, 22–43 (2008)CrossRefGoogle Scholar
  25. 25.
    Ahmed, A., Farag, A.: A new formulation for shape from shading for non-lambertian surfaces. In: Proc. IEEE CVPR (2006)Google Scholar
  26. 26.
    Tsai, P.S., Shah, M.: Shape from shading using linear approximation. Image and Vision Computing 12, 487–498 (1994)CrossRefGoogle Scholar
  27. 27.
    Tagare, H., Defigueiredo, R.: A theory of photometric stereo for a class of diffuse non-lambertian surfaces. IEEE Trans. PAMI 13, 133–152 (1991)CrossRefGoogle Scholar
  28. 28.
    Goldman, D., Curless, B., Hertzmann, A., Seitz, S.: Shape and spatially-varying BRDFs from photometric stereo. IEEE Trans. PAMI 32, 1060–1071 (2010)CrossRefGoogle Scholar
  29. 29.
    Sato, Y., Ikeuchi, K.: Temporal-color space analysis of reflection. JOSA A 11, 2990–3002 (1994)CrossRefGoogle Scholar
  30. 30.
    Zickler, T., Mallick, S., Kriegman, D., Belhumeur, P.: Color subspaces as photometric invariants. IJCV 79, 13–30 (2008)CrossRefGoogle Scholar
  31. 31.
    Frankot, R., Chellappa, R.: A method for enforcing integrability in shape from shading algorithms. IEEE Trans. PAMI 10, 439–451 (1988)zbMATHCrossRefGoogle Scholar
  32. 32.
    Hayakawa, H.: Photometric stereo under a light-source with arbitrary motion. JOSA-A 11, 3079–3089 (1994)CrossRefGoogle Scholar
  33. 33.
    Yuille, A., Snow, D.: Shape and albedo from multiple images using integrability. In: Proc. IEEE CVPR (1997)Google Scholar
  34. 34.
    Belhumeur, P., Kriegman, D., Yuille, A.: The bas-relief ambiguity. IJCV 35 (1999)Google Scholar
  35. 35.
    Chandraker, M., Kahl, F., Kriegman, D.: Reflections on the generalized bas-relief ambiguity. In: Proc. IEEE CVPR (2005)Google Scholar
  36. 36.
    Alldrin, N.G., Mallick, S., Kriegman, D.: Resolving the generalized bas-relief ambiguity by entropy minimization. In: Proc. IEEE CVPR (2007)Google Scholar
  37. 37.
    Tan, P., Mallick, S., Quan, L., Kriegman, D., Zickler, T.: Isotropy, reciprocity and the generalized bas-relief ambiguity. In: Proc. IEEE CVPR (2007)Google Scholar
  38. 38.
    Nayar, S., Fang, X., Boult, T.: Separation of reflection components using color and polarization. IJCV 21, 163–186 (1997)CrossRefGoogle Scholar
  39. 39.
    Zickler, T., Mallick, S., Kriegman, D., Belhumeur, P.N.: Color subspaces as photometric invariants. IJCV 79, 13–30 (2008)CrossRefGoogle Scholar
  40. 40.
    Drbohlav, O., Chaniler, M.: Can two specular pixels calibrate photometric stereo? In: Proc. IEEE ICCV (2005)Google Scholar
  41. 41.
    Nayar, S., Krishnan, G., Grossberg, M., Raskar, R.: Fast separation of direct and global components of a scene using high frequency illumination. ACM TOG 25, 935–944 (2006)Google Scholar
  42. 42.
    Forsyth, D., Zisserman, A.: Mutual illumination. In: Proc. IEEE CVPR (1989)Google Scholar
  43. 43.
    Nayar, S., Ikeuchi, K., Kanade, T.: Shape from interreflections. In: Proc. IEEE ICCV (1990)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tali Treibitz
    • 1
  • Zak Murez
    • 1
  • B. Greg Mitchell
    • 2
  • David Kriegman
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of CaliforniaSan DiegoUSA
  2. 2.Scripps Institution of OceanographyUniversity of CaliforniaSan DiegoUSA

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