skip to main content
research-article

Acquiring reflectance and shape from continuous spherical harmonic illumination

Published:21 July 2013Publication History
Skip Abstract Section

Abstract

We present a novel technique for acquiring the geometry and spatially-varying reflectance properties of 3D objects by observing them under continuous spherical harmonic illumination conditions. The technique is general enough to characterize either entirely specular or entirely diffuse materials, or any varying combination across the surface of the object. We employ a novel computational illumination setup consisting of a rotating arc of controllable LEDs which sweep out programmable spheres of incident illumination during 1-second exposures. We illuminate the object with a succession of spherical harmonic illumination conditions, as well as photographed environmental lighting for validation. From the response of the object to the harmonics, we can separate diffuse and specular reflections, estimate world-space diffuse and specular normals, and compute anisotropic roughness parameters for each view of the object. We then use the maps of both diffuse and specular reflectance to form correspondences in a multiview stereo algorithm, which allows even highly specular surfaces to be corresponded across views. The algorithm yields a complete 3D model and a set of merged reflectance maps. We use this technique to digitize the shape and reflectance of a variety of objects difficult to acquire with other techniques and present validation renderings which match well to photographs in similar lighting.

Skip Supplemental Material Section

Supplemental Material

tp077.mp4

mp4

27.5 MB

References

  1. Adato, Y., Vasilyev, Y., Ben-Shahar, O., and Zickler, T. 2007. Toward a theory of shape from specular flow. In Proc. IEEE International Conference on Computer Vision, 1--8.Google ScholarGoogle Scholar
  2. Blake, A., and Brelstaff, G. 1992. In Physics-Based Vision, Principles and Practice: Shape Recovery, L. B. Wolff, S. A. Shafer, and G. E. Healey, Eds. Jones and Bartlett Publishers, Inc., USA, ch. Geometry from specularities, 277--286. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bonfort, T., and Sturm, P. 2003. Voxel carving for specular surfaces. In Proc. IEEE International Conference on Computer Vision, 591--596. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Chen, T., Goesele, M., and Seidel, H. P. 2006. Mesostructure from specularities. In CVPR, 1825--1832. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dana, K. J., van Ginneken, B., Nayar, S. K., and Koenderink, J. J. 1999. Reflectance and texture of real-world surfaces. ACM Trans. Graph. 18, 1 (Jan.), 1--34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Debevec, P., Hawkins, T., Tchou, C., Duiker, H.-P., Sarokin, W., and Sagar, M. 2000. Acquiring the reflectance field of a human face. In Proceedings of ACM SIGGRAPH 2000, 145--156. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Dong, Y., Wang, J., Tong, X., Snyder, J., Lan, Y., Ben-Ezra, M., and Guo, B. 2010. Manifold bootstrapping for svbrdf capture. ACM Trans. Graph. 29 (July), 98:1--98:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Francken, Y., Cuypers, T., Mertens, T., Gielis, J., and Bekaert, P. 2008. High quality mesostructure acquisition using specularities. CVPR, 1--7.Google ScholarGoogle Scholar
  9. Furukawa, Y., and Ponce, J. 2009. Dense 3D motion capture for human faces. In Proc. of CVPR 09.Google ScholarGoogle Scholar
  10. Gardner, A., Tchou, C., Hawkins, T., and Debevec, P. 2003. Linear light source reflectometry. In ACM TOG, 749--758. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Ghosh, A., Chen, T., Peers, P., Wilson, C. A., and Debevec, P. E. 2009. Estimating specular roughness and anisotropy from second order spherical gradient illumination. Comput. Graph. Forum 28, 4, 1161--1170. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Ghosh, A., Heidrich, W., Achutha, S., and O'Toole, M. 2010. A basis illumination approach to brdf measurement. Int. J. Comput. Vision 90, 2 (Nov.), 183--197. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Harris, C., and Stephens, M. 1988. A combined corner and edge detector. In Proc. of Fourth Alvey Vision Conference, 147--151.Google ScholarGoogle Scholar
  14. Hawkins, T., Einarsson, P., and Debevec, P. 2005. A dual light stage. In Proc. EGSR, 91--98. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Holroyd, M., Lawrence, J., Humphreys, G., and Zickler, T. 2008. A photometric approach for estimating normals and tangents. ACM Trans. Graph. 27, 5 (Dec.), 133:1--133:9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Holroyd, M., Lawrence, J., and Zickler, T. 2010. A coaxial optical scanner for synchronous acquisition of 3d geometry and surface reflectance. ACM Trans. Graph. 29, 4 (July), 99:1--99:12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ihrke, I., Kutulakos, K. N., Lensch, H. P. A., Magnor, M., and Heidrich, W. 2010. Transparent and specular object reconstruction. Computer Graphics Forum 29, 8, 2400--2426.Google ScholarGoogle ScholarCross RefCross Ref
  18. Ikeuchi, K. 1981. Determining surface orientations of specular surfaces by using the photometric stereo method. IEEE Trans. Pattern Anal. Mach. Intell. 3, 6 (June), 661--669. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Kolmogorov, V. 2006. Convergent tree-reweighted message passing for energy minimization. IEEE Trans. Pattern Anal. Mach. Intell. 28 (October), 1568--1583. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Lamond, B., Peers, P., Ghosh, A., and Debevec, P. 2009. Image-based separation of diffuse and specular reflections using environmental structured illumination. In Proc. IEEE International Conf. Computational Photography.Google ScholarGoogle Scholar
  21. Lensch, H. P. A., Kautz, J., Goesele, M., Heidrich, W., and Seidel, H.-P. 2003. Image-based reconstruction of spatial appearance and geometric detail. ACM TOG 22, 2, 234--257. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Ma, W.-C., Hawkins, T., Peers, P., Chabert, C.-F., Weiss, M., and Debevec, P. 2007. Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination. In Rendering Techniques, 183--194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Mcallister, D. K. 2002. A generalized surface appearance representation for computer graphics. PhD thesis, The University of North Carolina at Chapel Hill. AAI3061704. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Moré, J. J., Sorensen, D. C., Hillstrom, K. E., and Garbow, B. S. 1984. The MINPACK project. In Sources and Development of Mathematical Software, 88--111.Google ScholarGoogle Scholar
  25. Nayar, S., Ikeuchi, K., and Kanade, T. 1990. Determining shape and reflectance of hybrid surfaces by photometric sampling. IEEE Trans. Robotics and Automation 6, 4, 418--431.Google ScholarGoogle ScholarCross RefCross Ref
  26. Park, M., Kashyap, S., Collins, R., and Liu, Y. 2010. Data driven mean-shift belief propagation for non-gaussian mrfs. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, 3547--3554.Google ScholarGoogle Scholar
  27. Ramamoorthi, R., and Hanrahan, P. 2001. An efficient representation for irradiance environment maps. In Proc. of ACM SIGGRAPH '01, 497--500. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Ren, P., Wang, J., Snyder, J., Tong, X., and Guo, B. 2011. Pocket reflectometry. ACM Trans. Graph. 30, 4 (July), 45:1--45:10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Sato, Y., Wheeler, M. D., and Ikeuchi, K. 1997. Object shape and reflectance modeling from observation. In Proceedings of the 24th annual conference on Computer graphics and interactive techniques, ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, SIGGRAPH '97, 379--387. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Sloan, P.-P., 2008. Stupid spherical harmonics (sh) tricks. Game Developer's Conference, Feb. http://www.ppsloan.org/publications/.Google ScholarGoogle Scholar
  31. Tarini, M., Lensch, H. P., Goesele, M., and Seidel, H.-P. 2005. 3D acquisition of mirroring objects using striped patterns. Graphical Models 67, 4, 233--259. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Wang, C.-P., Snavely, N., and Marschner, S. 2011. Estimating dual-scale properties of glossy surfaces from step-edge lighting. ACM Trans. Graph. (Proc. SIGGRAPH Asia) 30, 6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Ward, G. J. 1992. Measuring and modeling anisotropic reflection. SIGGRAPH Comput. Graph. 26, 2, 265--272. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Westin, S. H., Arvo, J. R., and Torrance, K. E. 1992. Predicting reflectance functions from complex surfaces. SIGGRAPH Comput. Graph. 26, 2 (July), 255--264. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Weyrich, T., Lawrence, J., Lensch, H. P. A., Rusinkiewicz, S., and, T. 2009. Principles of appearance acquisition and representation. Found. Trends. Comput. Graph. Vis. 4, 2 (Feb.), 75--191. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Woodham, R. J. 1980. Photometric method for determining surface orientation from multiple images. Optical Engineering 19, 1, 139--144.Google ScholarGoogle ScholarCross RefCross Ref
  37. Zickler, T. E., Belhumeur, P. N., and Kriegman, D. J. 2002. Helmholtz stereopsis: Exploiting reciprocity for surface reconstruction. Int. J. Comput. Vision 49, 2-3, 215--227. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Zickler, T., Ramamoorthi, R., Enrique, S., and Belhumeur, P. N. 2006. Reflectance sharing: Predicting appearance from a sparse set of images of a known shape. PAMI 28, 8, 1287--1302. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Acquiring reflectance and shape from continuous spherical harmonic illumination

        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 32, Issue 4
          July 2013
          1215 pages
          ISSN:0730-0301
          EISSN:1557-7368
          DOI:10.1145/2461912
          Issue’s Table of Contents

          Copyright © 2013 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 the author(s) 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: 21 July 2013
          Published in tog Volume 32, Issue 4

          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