“The influence of shape on the perception of material reflectance” by Vangorp, Laurijssen and Dutré

  • ©Peter Vangorp, Jurgen Laurijssen, and Philip Dutré

Conference:


Type:


Title:

    The influence of shape on the perception of material reflectance

Presenter(s)/Author(s):



Abstract:


    Visual observation is our principal source of information in determining the nature of objects, including shape, material or roughness. The physiological and cognitive processes that resolve visual input into an estimate of the material of an object are influenced by the illumination and the shape of the object. This affects our ability to select materials by observing them on a point-lit sphere, as is common in current 3D modeling applications.In this paper we present an exploratory psychophysical experiment to study various influences on material discrimination in a realistic setting. The resulting data set is analyzed using a wide range of statistical techniques. Analysis of variance is used to estimate the magnitude of the influence of geometry, and fitted psychometric functions produce significantly diverse material discrimination thresholds across different shapes and materials.Suggested improvements to traditional material pickers include direct visualization on the target object, environment illumination, and the use of discrimination thresholds as a step size for parameter adjustments.

References:


    1. Aida, T. 1997. Glossiness of colored papers and its application to specular glossiness measuring instruments. Systems and Computers in Japan 28, 1, 95–112.Google ScholarCross Ref
    2. ASTM. 1999. Annual Book of ASTM Standards, volume 06.01. American Society for Testing and Materials.Google Scholar
    3. Ben-Artzi, A., Overbeck, R., and Ramamoorthi, R. 2006. Real-time BRDF editing in complex lighting. ACM Transactions on Graphics 25, 3, 945–954. Google ScholarDigital Library
    4. Brainard, D. H., and Wandell, B. A. 1991. A bilinear model of the illuminant’s effect on color appearance. In Computational Models of Visual Processing, M. S. Landy and J. A. Movshon, Eds. MIT Press, 171–186.Google Scholar
    5. Brainard, D. H., Pelli, D. G., and Robson, T. 2002. Display characterization. In Encyclopedia of Imaging Science and Technology, J. P. Hornak, Ed. Wiley, New York, 172–188.Google Scholar
    6. Brainard, D. H. 2004. Color constancy. In The Visual Neurosciences, L. M. Chalupa and J. S. Werner, Eds. MIT Press, 948–961.Google Scholar
    7. Colbert, M., PATTANAIK, S., and Krivanek, J. 2006. BRDF-Shop: Creating physically correct bidirectional reflectance distribution functions. IEEE Computer Graphics and Applications 26, 1, 30–36. Google ScholarDigital Library
    8. Debevec, P. E. 1998. Rendering synthetic objects into real scenes: Bridging traditional and image-based graphics with global illumination and high dynamic range photography. In Proceedings of ACM SIGGRAPH 98, ACM Press / ACM SIGGRAPH, New York, M. F. Cohen, Ed., Computer Graphics Proceedings, Annual Conference Series, ACM, 189–198. Google ScholarDigital Library
    9. Durand, F., Holzschuch, N., Soler, C., Chan, E., and Sillion, F. 2005. A frequency analysis of light transport. ACM Transactions on Graphics 24, 3, 1115–1126. Google ScholarDigital Library
    10. Dutré, P., Bala, K., and Bekaert, P. 2006. Advanced Global Illumination, 2nd ed. A K Peters, Natick, MA. Google ScholarDigital Library
    11. Efron, B. 1979. Bootstrap methods: another look at the jackknife. Annals of Statistics 7, 1, 1–26.Google ScholarCross Ref
    12. Ferwerda, J. A., Pellacini, F., and Greenberg, D. P. 2001. A psychophysically-based model of surface gloss perception. In Proceedings of SPIE Human Vision and Electronic Imaging, 291–301.Google Scholar
    13. Fleming, R. W., Dror, R. O., and Adelson, E. H. 2003. Real-world illumination and the perception of surface reflectance properties. Journal of Vision 3, 5, 347–368.Google ScholarCross Ref
    14. Foster, D. H. 2003. Does colour constancy exist? Trends in Cognitive Sciences 7, 10, 439–443.Google ScholarCross Ref
    15. Kruskal, W. H., and Wallis, W. A. 1952. Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association 47, 260, 583–621.Google ScholarCross Ref
    16. Longhurst, P., Ledda, P., and Chalmers, A. 2003. Psychophysically based artistic techniques for increased perceived realism of virtual environments. In Proceedings of Afrigraph, Afrigraph, 123–132. Google ScholarDigital Library
    17. Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2003. A data-driven reflectance model. ACM Transactions on Graphics 22, 3, 759–769. Google ScholarDigital Library
    18. Matusik, W., Pfister, H., Brand, M., and McMillan, L. 2003. Efficient isotropic BRDF measurement. In Proceedings of the 14th Eurographics Symposium on Rendering, P. Dutré, F. Suykens, P. H. Christensen, and D. Cohen-Or, Eds., Eurographics, 241–248. Google ScholarDigital Library
    19. Ngan, A., Durand, F., and Matusik, W. 2005. Experimental analysis of BRDF models. In Proceedings of the 16th Eurographics Symposium on Rendering 2005, K. Bala and P. Dutré, Eds., Eurographics, 117–126. Google ScholarCross Ref
    20. Ngan, A., Durand, F., and Matusik, W. 2006. Image-driven navigation of analytical BRDF models. In Proceedings of the 17th Eurographics Symposium on Rendering, T. Akenine-Möller and W. Heidrich, Eds., Eurographics, 399–407. Google ScholarCross Ref
    21. Nicodemus, F. E., Richmond, J. C., Hsia, J. J., Ginsberg, I. W., and Limperis, T. 1977. Geometrical Considerations and Nomenclature for Reflectance. Monograph 160, National Bureau of Standards.Google Scholar
    22. Nishida, S., and Shinya, M. 1998. Use of image-based information in judgments of surface-reflectance properties. Journal of the Optical Society of America A: Optics, Image Science & Vision 15, 12, 2951–2965.Google ScholarCross Ref
    23. Obein, G., Knoblauch, K., and Viénot, F. 2004. Difference scaling of gloss: Nonlinearity, binocularity, and constancy. Journal of Vision 4, 9, 711–720.Google ScholarCross Ref
    24. Palmer, S. E. 1975. Visual perception and world knowledge: Notes on a model of sensory-cognitive interaction. Freeman, San Francisco, 279–307.Google Scholar
    25. Pellacini, F., Ferwerda, J. A., and Greenberg, D. P. 2000. Toward a psychophysically-based light reflection model for image synthesis. In Proceedings of ACM SIGGRAPH 2000, ACM Press / ACM SIGGRAPH, New York, K. Akeley, Ed., Computer Graphics Proceedings, Annual Conference Series, ACM, 55–64. Google ScholarDigital Library
    26. Ramamoorthi, R., Mahajan, D., and Belhumeur, P. 2007. A first-order analysis of lighting, shading, and shadows. ACM Transactions on Graphics 26, 1. Google ScholarDigital Library
    27. Ward Larson, G., Rushmeier, H., and Piatko, C. 1997. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics 3, 4, 291–306. Google ScholarDigital Library
    28. Ward, G. J. 1992. Measuring and modeling anisotropic reflection. Computer Graphics (Proceedings of ACM SIGGRAPH 92) 26, 2, 265–272. Google ScholarDigital Library
    29. Weibull, W. 1951. A statistical distribution function of wide applicability. Journal of Applied Mechanics 18, 3, 293–297.Google ScholarCross Ref
    30. Westlund, H. B., and Meyer, G. W. 2001. Applying appearance standards to light reflection models. In Proceedings of ACM SIGGRAPH 2001, ACM Press / ACM SIGGRAPH, New York, E. Fiume, Ed., Computer Graphics Proceedings, Annual Conference Series, ACM, 501–510. Google ScholarDigital Library
    31. Wichmann, F. A., and Hill, N. J. 2001. The psychometric function: I. Fitting, sampling, and goodness of fit. Perception & Psychophysics 63, 8, 1293–1313.Google Scholar
    32. Wichmann, F. A., and Hill, N. J. 2001. The psychometric function: II. Bootstrap-based confidence intervals and sampling. Perception & Psychophysics 63, 8, 1314–1329.Google Scholar
    33. Xiao, B., and Brainard, D. H. 2006. Color perception of 3D objects: Constancy with respect to variation of surface gloss. In Symposium on Applied Perception in Graphics and Visualisation 2006, ACM, 63–68. Google ScholarDigital Library


ACM Digital Library Publication:



Overview Page: