Abstract
We introduce a new methodology for radiometric reconstruction from multiple images. It opens new possibilities because it allows simultaneous recovery of varying unknown illuminants (one per image), surface albedoes, and cameras’ radiometric responses. Designed to complement geometric reconstruction techniques, it only requires as input the geometry of the scene and of the cameras. Unlike photometric stereo approaches, it is not restricted to images taken from a single viewpoint. Linear and non-linear implementations in the Lambertian case are proposed; simulation results are discussed and compared to related work to demonstrate the gain in stability; and results on real images are shown.
This work was sponsored in part by the Defense Advanced Research Projects Agency under contract F33615-97-C-1023 monitored by Wright Laboratory and in part by the Swiss Federal Office for Education and Science. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency, the United States Government, SRI International or EPFL.
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References
E. Angelopoulou and J. Williams. Photometric surface analysis in a tri-luminal environment. In ICCV, pages 442–447, 1999.
R. Baribeau, M. Rioux, and G. Godin. Color reflectance modeling using a polychromatic laser range sensor. PAMI, 14(2):263–269, 1992.
P.N. Belhumeur, D.J. Kriegman, and A.L. Yuille. The bas-relief ambiguity. IJCV, 35(1):33–44, November 1999.
P. Debevec and J. Malik. Recovering high dynamic range radiance maps from photographs. SIGGRAPH, 31:369–378, 1997.
M.A Fischler and R.C Bolles. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Communications ACM, 24(6):381–395, 1981.
P. Fua. Regularized Bundle-Adjustment to Model Heads from Image Sequences without Calibration Data. International Journal of Computer Vision, 38(2):153–171, July 2000.
A.S. Georghiades, P.N. Belhumeur, and D.J. Kriegman. Illumination-based image synthesis: Creating novel images of human faces under differing pose and lighting. In IEEE Workshop on multiple-view modeling and analysis of visual scenes, pages 47–54, 1999.
H. Hayakawa. Photometric stereo under a light-source with arbitrary motion. JOSA-A, 11(11):3079–3089, November 1994.
B.K.P. Horn. Robot Vision. MIT Press, 1986.
B.K.P. Horn and M.J. Brooks. Shape from Shading. MIT Press, 1989.
K. Ikeuchi and K. Sato. Determining reflectance properties of an object using range and brightness images. PAMI, 13(11):1139–1153, 1991.
Q.T. Luong, P. Fua, and Y. G. Leclerc. The Radiometry of Multiple Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(1):19–33, January 2002.
S. Marschner. Inverse rendering for computer graphics. PhD thesis, Cornell University, 1998.
S. Marschner and D. Greenberg. Inverse lighting for photography. In IST/SID Fifth Color Imaging Conference, pages 262–265, 1997.
T. Mitsunaga and S.K. Nayar. Radiometric self calibration. In CVPR, pages I:374–380, 1999.
Y. Moses. Face recognition: generalization to novel images. PhD thesis, The Weizmann Institute of Science, Israel, 1993.
N. Mukawa. Estimation of shape, reflection coefficients and illuminant direction from image sequences. In ICCV, pages 507–512, 1990.
K. Nishino, Z. Zhang, and K. Ikeuchi. Determining Reflectance Parameters and Illumination Distribution from a Sparse Set of Images for View-Dependent Image Synthesis. In International Conference on Computer Vision, pages 599–606, Vancouver, Canada, July 2001.
R Ramamoorthi and P. Hanrahan. A signal processing framework for inverse rendering. In SIGGRAPH, pages 117–128, 2001.
I. Sato, Y. Sato, and K. Ikeuchi. Illumination distribution from brightness in shadows: Adaptive estimation of illumination distribution with unknown reflectance properties in shadow regions. In ICCV, pages 875–883, 1999.
M. Sato, Y. Wheeler and K. Ikeuchi. Object shape and reflectance modeling from observation. In SIGGRAPH, pages 379–387, 1997.
A. Shashua. On photometric issues in 3d visual recognition from a single 2d image. IJCV, 21(1–2):99–122, 1997.
W. Silver. Determining shape and reflectance using multiple images. PhD thesis, MIT, Cambridge, MA, 1990.
R.J. Woodham. Photometric method for determining surface orientation from multiple images. OptEng, 19(1):139–144, 1980.
Y. Yu, P. Debevec, J. Malik, and T. Hawkins. Inverse global illumination: Recovering reflectance models of real scenes from photographs. SIGGRAPH, pages 215–224, August 1999.
A.L. Yuille, D. Snow, R. Epstein, and P.N. Belhumeur. Determining generative models of objects under varying illumination: Shape and albedo from multiple images using svd and integrability. IJCV, 35(3):1–20, 1999.
Q. Zheng and R. Chellappa. Estimation of illuminant direction, albedo, and shape from shading. PAMI, 13(7):680–702, 1991.
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Luong, QT., Fua, P., Leclerc, Y. (2002). Recovery of Reflectances and Varying Illuminants from Multiple Views. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47977-5_11
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