skip to main content
research-article
Open Access

Physically-accurate fur reflectance: modeling, measurement and rendering

Published:02 November 2015Publication History
Skip Abstract Section

Abstract

Rendering photo-realistic animal fur is a long-standing problem in computer graphics. Considerable effort has been made on modeling the geometric complexity of fur, but the reflectance of fur fibers is not well understood. Fur has a distinct diffusive and saturated appearance, that is not captured by either the Marschner hair model or the Kajiya-Kay model. In this paper, we develop a physically-accurate reflectance model for fur fibers. Based on anatomical literature and measurements, we develop a double cylinder model for the reflectance of a single fur fiber, where an outer cylinder represents the biological observation of a cortex covered by multiple cuticle layers, and an inner cylinder represents the scattering interior structure known as the medulla. Our key contribution is to model medulla scattering accurately---in contrast, for human hair, the medulla has minimal width and thus negligible contributions to the reflectance. Medulla scattering introduces additional reflection and transmission paths, as well as diffusive reflectance lobes. We validate our physical model with measurements on real fur fibers, and introduce the first database in computer graphics of reflectance profiles for nine fur samples. We show that our model achieves significantly better fits to the measured data than the Marschner hair reflectance model. For efficient rendering, we develop a method to precompute 2D medulla scattering profiles and analytically approximate our reflectance model with factored lobes. The accuracy of the approach is validated by comparing our rendering model to full 3D light transport simulations. Our model provides an enriched set of controls, where the parameters we fit can be directly used to render realistic fur, or serve as a starting point from which artists can manually tune parameters for desired appearances.

Skip Supplemental Material Section

Supplemental Material

References

  1. Carrlee, E., and Horelick, L. 2011. The alaska fur id project: A virtual resource for material identification. In Objects Specialty Group Postprints, American Institute for Conservation of Historic and Artistic Works, vol. 18, 149--171.Google ScholarGoogle Scholar
  2. Davis, A. 2006. Effective propagation kernels in structured media with broad spatial correlations, illustration with large-scale transport of solar photons through cloudy atmospheres. In Computational Methods in Transport, F. Graziani, Ed., vol. 48 of Lecture Notes in Computational Science and Engineering. Springer Berlin Heidelberg, 85--140.Google ScholarGoogle Scholar
  3. Deedrick, D. W., and Koch, S. L. 2004. Microscopy of hair part 1: A practical guide and manual for human hairs. Forensics Science Communication.Google ScholarGoogle Scholar
  4. Deedrick, D. W., and Koch, S. L. 2004. Microscopy of hair part ii: a practical guide and manual for animal hairs. Forensics Science Communication.Google ScholarGoogle Scholar
  5. d'Eon, E., Francois, G., Hill, M., Letteri, J., and Aubry, J.-M. 2011. An energy-conserving hair reflectance model. In EGSR 11, 1181--1187. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. d'Eon, E., Marschner, S., and Hanika, J. 2013. Importance sampling for physically-based hair fiber models. In SIGGRAPH Asia 2013 Technical Briefs, 25:1--25:4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. d'Eon, E., Marschner, S., and Hanika, J. 2014. A fiber scattering model with non-separable lobes. In ACM SIGGRAPH 2014 Talks, 46:1--46:1. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Donner, C., Lawrence, J., Ramamoorthi, R., Hachisuka, T., Jensen, H. W., and Nayar, S. 2009. An empirical BSSRDF model. ACM Trans. Graph. 28, 3, 30:1--30:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Galatk, A., Galatk, J., Krul, Z., and Galatk Jr, A., 2011. Furskin identification. http://www.furskin.cz.Google ScholarGoogle Scholar
  10. Goldman, D. B. 1997. Fake fur rendering. In SIGGRAPH 97, 127--134. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hashimoto, K. 1988. The structure of human hair. Clinics in Dermatology 6, 4, 7--21.Google ScholarGoogle ScholarCross RefCross Ref
  12. Hery, C., and Ramamoorthi, R. 2012. Importance sampling of reflection from hair fibers. Journal of Computer Graphics Techniques (JCGT) 1, 1, 1--17.Google ScholarGoogle Scholar
  13. Jakob, W., 2010. Mitsuba renderer. http://www.mitsubarenderer.org.Google ScholarGoogle Scholar
  14. Kajiya, J. T., and Kay, T. L. 1989. Rendering fur with three dimensional textures. In SIGGRAPH 89, 271--280. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Khungurn, P., and Marschner, S. 2015. Azimuthal scattering from elliptical hair fibers. Accepted to ACM Transactions on Graphics with minor revisions.Google ScholarGoogle Scholar
  16. Lokovic, T., and Veach, E. 2000. Deep shadow maps. In SIGGRAPH 00, 385--392. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Marschner, S. R., Jensen, H. W., Cammarano, M., Worley, S., and Hanrahan, P. 2003. Light scattering from human hair fibers. ACM Trans. Graph. 22, 3, 780--791. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Moon, J. T., and Marschner, S. R. 2006. Simulating multiple scattering in hair using a photon mapping approach. ACM Trans. Graph. 25, 3, 1067--1074. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Nguyen, H., and Donnelly, W. 2005. Hair animation and rendering in the nalu demo. GPU Gems 2, 361--380.Google ScholarGoogle Scholar
  20. Ogaki, S., Tokuyoshi, Y., and Schoellhammer, S. 2010. An empirical fur shader. In ACM SIGGRAPH ASIA 2010 Sketches, ACM, 16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Ou, J., Xie, F., Krishnamachari, P., and Pellacini, F. 2012. Ishair: Importance sampling for hair scattering. In ACM SIGGRAPH 2012 Talks, 28:1--28:1. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Peers, P., vom Berge, K., Matusik, W., Ramamoorthi, R., Lawrence, J., Rusinkiewicz, S., and Dutré, P. 2006. A compact factored representation of heterogeneous subsurface scattering. ACM Trans. Graph. 25, 3, 746--753. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Qin, H., Chai, M., Hou, Q., Ren, Z., and Zhou, K. 2014. Cone tracing for furry object rendering. Visualization and Computer Graphics, IEEE Transactions on 20, 8, 1178--1188. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Ren, P., Wang, J., Gong, M., Lin, S., Tong, X., and Guo, B. 2013. Global illumination with radiance regression functions. ACM Trans. Graph. 32, 4, 130:1--130:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sadeghi, I., Pritchett, H., Jensen, H. W., and Tamstorf, R. 2010. An artist friendly hair shading system. ACM Trans. Graph. 29, 4, 56:1--56:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Sadeghi, I., Bisker, O., De Deken, J., and Jensen, H. W. 2013. A practical microcylinder appearance model for cloth rendering. ACM Trans. Graph. 32, 2, 14:1--14:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Sintorn, E., and Assarsson, U. 2009. Hair self shadowing and transparency depth ordering using occupancy maps. In Symposium on Interactive 3D Graphics and Games, 67--74. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sloan, P.-P., Kautz, J., and Snyder, J. 2002. Precomputed radiance transfer for real-time rendering in dynamic, low-frequency lighting environments. ACM Trans. Graph. 21, 3, 527--536. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Stam, J. 1995. Multiple scattering as a diffusion process. In Rendering Techniques 95. 41--50.Google ScholarGoogle Scholar
  30. Stamm, R. F., Garcia, M. L., and Fuchs, J. J. 1977. The optical properties of human hair i. fundamental considerations and goniophotometer curves. Journal of the Society of Cosmetic Chemists 28, 9, 571--599.Google ScholarGoogle Scholar
  31. Stokes, G. G. 1860. On the intensity of the light reflected from or transmitted through a pile of plates. Proceedings of the Royal Society of London 11, 545--556.Google ScholarGoogle Scholar
  32. Tseng, C.-W. 2015. A Physically-Based Reflectance Model For Mammalian Fur Fibers Based On Anatomy And Gonioreflectometry Measurements. Master's thesis, University of California San Diego.Google ScholarGoogle Scholar
  33. Wang, R., Tran, J., and Luebke, D. 2005. All-frequency interactive relighting of translucent objects with single and multiple scattering. ACM Trans. Graph. 24, 3, 1202--1207. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Wei, X., 2006. What is human hair? a light and scanning electron microscopy study.Google ScholarGoogle Scholar
  35. Xu, K., Ma, L.-Q., Ren, B., Wang, R., and Hu, S.-M. 2011. Interactive hair rendering and appearance editing under environment lighting. ACM Transactions on Graphics 30, 6, 173:1--173:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Yuksel, C., and Keyser, J. 2008. Deep opacity maps. Computer Graphics Forum 27, 2, 675--680.Google ScholarGoogle ScholarCross RefCross Ref
  37. Zinke, A., and Weber, A. 2007. Light scattering from filaments. IEEE Transactions on Visualization and Computer Graphics 13, 2, 342--356. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Zinke, A., Yuksel, C., Weber, A., and Keyser, J. 2008. Dual scattering approximation for fast multiple scattering in hair. ACM Trans. Graph. 27, 3, 32:1--32:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Zinke, A., Rump, M., Lay, T., Weber, A., Andriyenko, A., and Klein, R. 2009. A practical approach for photometric acquisition of hair color. ACM Trans. Graph. 28, 5, 165:1--165:9. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Physically-accurate fur reflectance: modeling, measurement and rendering

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    • Published in

      cover image ACM Transactions on Graphics
      ACM Transactions on Graphics  Volume 34, Issue 6
      November 2015
      944 pages
      ISSN:0730-0301
      EISSN:1557-7368
      DOI:10.1145/2816795
      Issue’s Table of Contents

      Copyright © 2015 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 2 November 2015
      Published in tog Volume 34, Issue 6

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader