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Abstrakty
EN
A human observer is able to determine the color of objects independent of the light illuminating these objects. This ability is known as color constancy. In the first stages of visual information processing, data are analyzed with respect to wavelength composition, orientation, motion, and depth. With this contribution, we investigate whether depth information can help in estimating the color of the objects. We assume that local space average color is computed in V4 through resistively coupled neurons to estimate the color of the illuminant. We show how this computational model can be extended to incorporate depth information.
Rocznik
Strony
167--177
Opis fizyczny
Bibliogr. 47 poz., rys., zdj.
Twórcy
autor
  • Institut für Mathematik und Informatik, Ernst Moritz Arndt Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany
autor
  • Institut für Mathematik und Informatik, Ernst Moritz Arndt Universität Greifswald, Walther-Rathenau-Straße 47, 17487 Greifswald, Germany
Bibliografia
  • 1. McCann JJ. Simultaneous contrast and color constancy: signatures of human image processing. In: Davis S, editor. Color perception: philosophical, psychological, artistic, and computational perspectives. Volume 9. Vancouver studies in cognitive science. Oxford: Oxford University Press, 2000: 87-101.
  • 2. McCann JJ, McKee SP, Taylor TH. Quantitative studies in retinex theory. Vis Res 1976;16:445-58.
  • 3. Zeki S. A vision of the brain. Oxford: Blackwell Science, 1993.
  • 4. Ebner M. Color constancy. England: John Wiley & Sons, 2007.
  • 5. Brainard DH, Freeman WT. Bayesian color constancy. J Opt Soc Am A 1997;14:1393-411.
  • 6. Finlayson GD, Hordley SD. Color constancy at a pixel. J Opt Soc Am A 2001;18:253-64.
  • 7. Finlayson GD, Hordley S, Pubel PM. Color by correlation: a simple, unifying framework for color constancy. IEEE Trans Pattern Anal Machine Intell 2001;23:1209-21.
  • 8. Forsyth DA. A novel algorithm for color constancy. Int J Comput Vis 1990:5:5-36.
  • 9. Funt BV, Drew MS, Ho J. Color constancy from mutual reflection. Int J Comput Vis 1991:6:5-24
  • 10. Geusebroek JM, van den Boomgaard R, Smeulders AW, Geerts H. Color invariance. IEEE Trans Pattern Anal Machine Intell 2001:23:1338-50.
  • 11. Funt B, Cardei V, Barnard K. Learning color constancy. In: Proceedings of the IS&T/SID Fourth Color Imaging Conference, Scottsdale, 1996:58-60.
  • 12. Hurlbert AC, Poggio TA. Synthesizing a color algorithm from examples. Science 1988:239:482-3.
  • 13. Cardei VC, Funt B. Committee-based color constancy. In: 35. Proceedings of the IS&T/SID Seventh Color Imaging Conference: Color Science, Systems and Applications, Scottsdale, AZ, 1999:311-3.
  • 14. Lu R, Gijsenij A, Gevers T, Nedović V, Xu D, Geusebroek JM. Color constancy using 3d scene geometry. In: Proceedings of the 12th IEEE International Conference on Computer Vision, Kyoto, Japan, 2009:1749-56.
  • 15. Barnard K, Cardei V, Funt B. A comparison of computational color constancy algorithms - part I: methodology and experiments with synthesized data. IEEE Trans Image Process 2002:11:972-84
  • 16. Barnard K, Martin L, Coath A, Funt B. A comparison of computational color constancy algorithms - part II: experiments with image data. IEEE Trans Image Process 2002:11:985-96.
  • 17. Funt B, Barnard K, Martin L. Is machine colour constancy good enough? In: Burkhardt H, Neumann B, editors. Fifth European Conference on Computer Vision (ECCV'98), Freiburg, Germany. Berlin: Springer-Verlag, 1998:445-59.
  • 18. Buchsbaum G. A spatial processor model for object colour perception. J Franklin Inst 1980:310:337-50.
  • 19. van de Weijer J, Gevers T, Gijsenij A. Edge-based color constancy. IEEE Trans Image Process 2007;16:2207-14.
  • 20. Barnard K, Finlayson G, Funt B. Color constancy for scenes with varying illumination. Comput Vis Image Understand 1997:65:311-21.
  • 21. Land EH, McCann JJ. Lightness and retinex theory. J Opt Soc Am 1971:61:1-11.
  • 22. Blake A. Boundary conditions for lightness computation in Mondrian world. Comput Vis Graphics Image Process 1985:32:314-27.
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  • 29. Ebner M. Color constancy based on local space average color. Machine Vis Appl J 2009:20:283-301.
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  • 31. Ebner M. Estimating the color of the illuminant using anisotropic diffusion. In: Kropatsch WG, Kampel M, Hanbury A, editors. Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns, August 27-29, 2007, Vienna, Austria. Berlin: Springer-Verlag, 2007:441-9.
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  • 35. Microsoft Corporation. Programming with the Kinect for Windows SDK. Redmond, WA: Microsoft Corporation, 2011.
  • 36. Ebner M. A parallel algorithm for color constancy. J Parallel Distrib Comput 2004:64:79-88.
  • 37. Ebner M. How does the brain arrive at a color constant descriptor? In: Mele F, Ramella G, Santillo S, Ventriglia F, editors. Proceedings of the 2nd International Symposium on Brain, Vision and Artificial Intelligence, October 10-12, 2007, Naples, Italy. Berlin: Springer, 2007:84-93.
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  • 39. Gegenfurtner KR. Cortical mechanisms of colour vision. Nat Rev Neurosci 2003:4:563-72.
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  • 42. Livingstone MS, Hubel DH. Anatomy and physiology of a color system in the primate visual cortex. J Neurosci 1984:4:309-56.
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  • 44. Kofler M. Inbetriebahme und Untersuchung des Kinect Sensors. Master's thesis. Österreich: FH Oberösterreich, 2011.
  • 45. Newcombe RA, Izadi S, Hilliges O, Molyneaux D, Kim D, Davison AJ, et al. Kinectfusion: real-time dense surface mapping and tracking. In: Proceedings of the 10th IEEE International Symposium on Mixed and Augmented Reality. New York: IEEE, 2011:127-36.
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Typ dokumentu
Bibliografia
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