“Discrete stochastic microfacet models” by Jakob, Marschner, Yan, Hasan, Ramamoorthi, et al. …

  • ©Wenzel Jakob, Steve Marschner, Ling-Qi Yan, Milos Hasan, Ravi Ramamoorthi, and Jason Lawrence

Conference:


Type:


Title:

    Discrete stochastic microfacet models

Session/Category Title: Reflectance: Modeling, Capturing, Renderings


Presenter(s)/Author(s):


Moderator(s):



Abstract:


    This paper investigates rendering glittery surfaces, ones which exhibit shifting random patterns of glints as the surface or viewer moves. It applies both to dramatically glittery surfaces that contain mirror-like flakes and also to rough surfaces that exhibit more subtle small scale glitter, without which most glossy surfaces appear too smooth in close-up. These phenomena can in principle be simulated by high-resolution normal maps, but maps with tiny features create severe aliasing problems under narrow-angle illumination. In this paper we present a stochastic model for the effects of random subpixel structures that generates glitter and spatial noise that behave correctly under different illumination conditions and viewing distances, while also being temporally coherent so that they look right in motion. The model is based on microfacet theory, but it replaces the usual continuous microfacet distribution with a discrete distribution of scattering particles on the surface. A novel stochastic hierarchy allows efficient evaluation in the presence of large numbers of random particles, without ever having to consider the particles individually. This leads to a multiscale procedural BRDF that is readily implemented in standard rendering systems, and which converges back to the smooth case in the limit.

References:


    1. Ashikhmin, M., and Shirley, P. 2000. An anisotropic Phong BRDF model. J. Graph. Tools 5, 2 (Feb.), 25–32. Google ScholarDigital Library
    2. Booth, J. 1844. IV. on the rectification and quadrature of the spherical ellipse. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 25, 163, 18–38.Google ScholarCross Ref
    3. Booth, J. 1852. Researches on the geometrical properties of elliptic integrals. Philosophical Transactions of the Royal Society of London 142, 311–416.Google ScholarCross Ref
    4. Boyd, S., and Vandenberghe, L. 2004. Convex Optimization. Cambridge University Press, New York, NY, USA. Google ScholarDigital Library
    5. Cook, R. L., and DeRose, T. 2005. Wavelet noise. ACM Trans. Graph. (SIGGRAPH 2005 Proceedings) 24, 3, 803–811. Google ScholarDigital Library
    6. Cook, R. L., and Torrance, K. E. 1981. A reflectance model for computer graphics. In Proceedings of SIGGRAPH ’81, ACM. Google ScholarDigital Library
    7. Dekker, N., Kirchner, E. J. J., Supèr, R., van den Kieboom, G. J., and Gottenbos, R. 2010. Total appearance differences for metallic and pearlescent materials: Contributions from color and texture. Color Research & Application 36, 1 (Dec.), 4–14. Google ScholarDigital Library
    8. Devroye, L. 1986. Non-Uniform Random Variate Generation. Springer-Verlag.Google Scholar
    9. Ershov, S., Khodulev, A., and Kolchin, K. 1999. Simulation of sparkles in metallic paints. In Proceedings of Graphicon 1999, 121–128.Google Scholar
    10. Ershov, S., Kolchin, K., and Myszkouwski, K. 2001. Rendering pearlescent appearance based on paint-composition modeling. Comp. Graphics Forum (Proc. EUROGRAPHICS) 20, 3.Google ScholarCross Ref
    11. Fairchild, M. D., and Johnson, G. M. 2005. On the salience of novel stimuli: Adaptation and image noise. In Proceedings of the IS&T/SID Color Imaging Conference, 333–338.Google Scholar
    12. Galassi, M. e. a. 2009. GNU Scientific Library Reference Manual, 3rd ed ed. Network Theory Ltd. Google ScholarDigital Library
    13. Günther, J., Chen, T., Goesele, M., Wald, I., and Seidel, H.-P. 2005. Efficient acquistion and realistic rendering of car paint. In VMV 2005 Proceedings.Google Scholar
    14. Han, C., Sun, B., Ramamoorthi, R., and Grinspun, E. 2007. Frequency domain normal map filtering. ACM Trans. Graph. (Proceedings of SIGGRAPH 2007) 26, 3, 28:1–28:12. Google ScholarDigital Library
    15. Igehy, H. 1999. Tracing ray differentials. In Proceedings of SIGGRAPH ’99, ACM Press/Addison-Wesley Publishing Co. Google ScholarDigital Library
    16. Jakob, W., 2010. Mitsuba renderer. http://www.mitsuba-renderer.org. Google ScholarDigital Library
    17. Kachitvichyanukul, V., and Schmeiser, B. W. 1988. Binomial random variate generation. Commun. ACM 31, 2 (Feb.), 216–222. Google ScholarDigital Library
    18. Keller, A., Premoze, S., and Raab, M. 2012. Advanced (quasi) monte carlo methods for image synthesis. In ACM SIGGRAPH 2012 Courses, ACM, SIGGRAPH ’12, 21:1–21:46. Google ScholarDigital Library
    19. Kirchner, E., van den Kieboom, G.-J., Njo, L., Supèr, R., and Gottenbos, R. 2007. Observation of visual texture of metallic and pearlescent materials. Color Research & Application 32, 4, 256–266.Google ScholarCross Ref
    20. Lagae, A., Lefebvre, S., Drettakis, G., and Dutré, P. 2009. Procedural noise using sparse Gabor convolution. ACM Trans. Graph. 28, 3 (July), 1. Google ScholarDigital Library
    21. McCamy, C. S. 1996. Observation and measurement of the appearance of metallic materials. Part I. Macro appearance. Color Research & Application 21, 4, 293.Google ScholarCross Ref
    22. McCamy, C. S. 1998. Observation and measurement of the appearance of metallic materials. Part II. Micro appearance. Color Research & Application 23, 6, 362–373. Google ScholarDigital Library
    23. Olano, M., and Baker, D. 2010. Lean mapping. In Proceedings of the 2010 ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, ACM, I3D ’10, 181–188. Google ScholarDigital Library
    24. Perlin, K. 2002. Improving noise. ACM Trans. Graph. (SIGGRAPH 2002 Proceedings) 21, 3, 681–682. Google ScholarDigital Library
    25. Rump, M., Müller, G., Sarlette, R., Koch, D., and Klein, R. 2008. Photo-realistic rendering of metallic car paint from image-based measurements. Computer Graphics Forum (EUROGRAPHICS Proceedings) 27, 2.Google ScholarCross Ref
    26. Schneider, P., and Eberly, D. H. 2002. Geometric tools for computer graphics. Morgan Kaufmann. Google ScholarDigital Library
    27. Toksvig, M. 2005. Mipmapping normal maps. Journal of Graphics Tools 10, 3, 65–71.Google ScholarCross Ref
    28. Torrance, K. E., and Sparrow, E. M. 1967. Theory for off-specular reflection from roughened surfaces. JOSA 57, 9, 1105–1112.Google ScholarCross Ref
    29. Veach, E. 1997. Robust Monte Carlo Methods for Light Transport Simulation. PhD thesis, Stanford University. Google ScholarDigital Library
    30. Walter, B., Marschner, S. R., Li, H., and Torrance, K. E. 2007. Microfacet models for refraction through rough surfaces. In Proceedings of the 18th Eurographics Conference on Rendering Techniques, 195–206. Google ScholarDigital Library
    31. Wheeler, D. J., and Needham, R. M. 1995. TEA, a tiny encryption algorithm. In Fast Software Encryption, Springer, 363–366.Google ScholarCross Ref
    32. Yan, L.-Q., Hašan, M., Jakob, W., Lawrence, J., Marschner, S., and Ramamoorthi, R. 2014. Rendering glints on high-resolution normal-mapped specular surfaces. ACM Trans. Graph. (Proceedings of SIGGRAPH 2014) 33, 4. Google ScholarDigital Library


ACM Digital Library Publication:



Overview Page: