Skip to main content

High Quality Final Gathering for Hierarchical Monte Carlo Radiosity for General Environments

  • Conference paper
Advances in Modelling, Animation and Rendering

Abstract

Aiming at rendering high quality images robustly for general environments with simple algorithms, we use a two-pass method that accounts for the global illumination. In this paper we present the integration of a new gathering procedure in the rendering pass, that uses the approximate results obtained by a particle tracing method, an extension of the Hierarchical Monte Carlo Radiosity (HMCR) algorithm. Results from our implementation demonstrate the efficient generation of high quality images using the technique presented herein.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J. Arvo. “Stratified Sampling of Spherical Triangles.” In Computer Graphics Proceedings, Annual Conference Series, 1995 (ACM SIGGRAPH ‘85 Proceedings), pages 437–438, 1995.

    Google Scholar 

  2. Ph. Bekaert, Ph. Dutré, and Y. D. Willems. “Final Radiosity Gather Step Using a Monte Carlo Technique with Optimal Importance Sampling.” Technical Report CW275, Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium, November 1998

    Google Scholar 

  3. Ph. Bekaert, L. Neumann, A. Neumann, M. Sbert, and Y. D. Willems.“Hierarchical Monte Carlo Radiosity.” In G. Drettakis and N. Max, editors,Rendering Techniques ‘88 (Proceedings of Eurographics Rendering Workshop ‘88), pages 259–268, New York, NY, 1998. Springer Wien.

    Google Scholar 

  4. P. Hanrahan, D. Salzman, and L. Aupperle. “A Rapid Hierarchical Radiosity Algorithm.” In Computer Graphics (ACM SIGGRAPH ‘81 Proceedings), volume 25, pages 197–206, July 1991.

    Article  Google Scholar 

  5. H. W. Jensen and P. H. Christensen. “Efficient Simulation of Light Transport in Scenes with Participating Media Using Photon Maps.” In Computer Graphics (ACM SIGGRAPH ‘88 Proceedings), pages 311–320, 1998.

    Google Scholar 

  6. S. N. Pattanaik and S. P. Mudur. “Computation of Global Illumination in a Participating Medium by Monte Carlo Simulation.” The Journal of Visualization and Computer Animation, 4(3):133–152, July - September 1993.

    Article  Google Scholar 

  7. F. Pérez, I. Martín, and X. Pueyo. “Hierarchical Monte Carlo Radiosity for General Environments.” Technical Report IiiA 02–01-RR, Institut d’Informàtica i Aplicacions, Universitat de Girona, Spain, 2002.

    Google Scholar 

  8. F. Pérez, I. Martín, F. X. Sillion, and X. Pueyo. “Acceleration of Monte Carlo Path Tracing in General Environments.” In Proceedings of Pacific Graphics 2000,Hong Kong, PRC, October 2000.

    Google Scholar 

  9. Jos Stam. Multi-Scale Stochastic Modelling of Complex Natural Phenomena. PhD thesis, University of Toronto, Dept. of Computer Science, 1995.

    Google Scholar 

  10. M. Stamminger, A. Scheel, X. Granier, F. Pérez, G. Drettakis, and F. Sillion. “Efficient Glossy Global Illumination with Interactive Viewing.” Computer Graphics Forum, 19(1):13–25, 2000.

    Article  Google Scholar 

  11. W. Sturzlinger. “Optimized Local Pass Using Importance Sampling.” In WSCG 96 (Fourth International Conference in Central Europe on Computer Graphics and Visualization),volume 2, pages 342–348, Plzen, Czech Republic, 1996. University of West Bohemia

    Google Scholar 

  12. C. Ureña and J. C. Torres. “Improved Irradiance Computation by Importance Sampling.” In J. Dorsey and Ph. Slusallek, editors, Rendering Techniques ‘87 (Proceedings of the Eighth Eurographics Workshop on Rendering), pages 275–284, New York, NY, 1997. Springer Wien. ISBN 275–284–275–284.

    Google Scholar 

  13. E. Veach. Robust Monte Carlo Methods for Light Transport Simulation. PhD thesis, Stanford University, December 1997.

    Google Scholar 

  14. C. Wang. “Physically Correct Direct Lighting for Distribution Ray Tracing.” In David Kirk, editor, Graphics Gems III, pages 307–313. Academic Press Professional, Boston, MA, 1992.

    Chapter  Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer-Verlag London

About this paper

Cite this paper

Pérez, F., Martín, I., Pueyo, X. (2002). High Quality Final Gathering for Hierarchical Monte Carlo Radiosity for General Environments . In: Vince, J., Earnshaw, R. (eds) Advances in Modelling, Animation and Rendering. Springer, London. https://doi.org/10.1007/978-1-4471-0103-1_27

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-0103-1_27

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1118-4

  • Online ISBN: 978-1-4471-0103-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics