Perceptual rendering of participating media

Abstract

High-fidelity image synthesis is the process of computing images that are perceptually indistinguishable from the real world they are attempting to portray. Such a level of fidelity requires that the physical processes of materials and the behavior of light are accurately simulated. Most computer graphics algorithms assume that light passes freely between surfaces within an environment. However, in many applications, we also need to take into account how the light interacts with media, such as dust, smoke, fog, etc., between the surfaces. The computational requirements for calculating the interaction of light with such participating media are substantial. This process can take many hours and rendering effort is often spent on computing parts of the scene that may not be perceived by the viewer. In this paper, we present a novel perceptual strategy for physically based rendering of participating media. By using a combination of a saliency map with our new extinction map (X map), we can significantly reduce rendering times for inhomogeneous media. The visual quality of the resulting images is validated using two objective difference metrics and a subjective psychophysical experiment. Although the average pixel errors of these metric are all less than 1%, the subjective validation indicates that the degradation in quality still is noticeable for certain scenes. We thus introduce and validate a novel light map (L map) that accounts for salient features caused by multiple light scattering around light sources.

References

1. Anson, O., Sundstedt, V., Gutierrez, D., and Chalmers, A. 2006. Efficient selective rendering of participating media. In APGV 06: Symposium on Applied Perception in Graphics and Visualization. ACM Press, New York. 135--142.
2. Bolin, M. R. and Meyer, G. W. 1995. A frequency based ray tracer. In SIGGRAPH. 409--418.
3. Bolin, M. R. and Meyer, G. W. 1998. A perceptually based adaptive sampling algorithm. Computer Graphics 32, Annual Conference Series, 299--309.
4. Cater, K., Chalmers, A., and Ward, G. 2003. Detail to attention: Exploiting visual tasks for selective rendering. In EGRW '03: Proc. of the 14th Eurographics Workshop on Rendering. Eurographics Association, Aire-la-Ville, Switzerland, Switzerland. 270--280.
5. Chalmers, A., Debattista, K., and Santos, L. P. 2006. Selective rendering: Computing only what you see. In Proceedings of GRAPHITE 2006, ACM SIGGRAPH.
6. Daly, S. 1993. The visible differences predictor: An algorithm for the assessment of image fidelity. In Digital Images and Human Vision. A.B. Watson, Ed. MIT Press, Cambridge, MA. 179--206.
7. Debattista, K. and Chalmers, A. 2005. Component-based adaptive sampling. In SIBGRAPI 2005. IEEE Computer Society Press, Los Alamitos, CA. 375--382.
8. Dumont, R., Pellacini, F., and Ferwerda, J. A. 2003. Perceptually-driven decision theory for interactive realistic rendering. ACM Trans. Graph. 22, 2, 152--181.
9. Ferwerda, J. A., Pattanaik, S. N., Shirley, P., and Greenberg, D. P. 1997. A model of visual masking for computer graphics. Computer Graphics 31, Annual Conference Series, 143--152.
10. Glassner, A. S. 1994. Principles of Digital Image Synthesis. Morgan Kaufmann, San Francisco, CA.
11. Gutierrez, D., Munoz, A., Anson, O., and Serón, F. J. 2005. Non-linear volume photon mapping. In Proc. of the Eurographics Symposium on Rendering Techniques, Konstanz, Germany, June 29--July 1, 2005. 291--300.
12. Haber, J., Myszkowski, K., Yamauchi, H., and Seidel, H.-P. 2001. Perceptually guided corrective splatting. In Computer Graphics Forum, Proc. of Eurographics 2001, A. Chalmers and T.-M. Rhyne, Eds. Computer Graphics Forum, vol. 20. Eurographics, Blackwell, Manchester, UK. C142--C152.
13. Itti, L., Koch, C., and Niebur, E. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20, 11, 1254--1259.
14. Jensen, H. W. and Christensen, P. H. 1998. Efficient simulation of light transport in scenes with participating media using photon maps. In SIGGRAPH 98 Conference Proceedings, M. Cohen, Ed. Annual Conference Series. ACM SIGGRAPH, Addison Wesley, Reading, MA. 311--320.
15. Kajiya, J. T. 1986. The rendering equation. In SIGGRAPH '86: Proc. of the 13th Annual Conference on Computer Graphics and Interactive Techniques. ACM Press, New York. 143--150.
16. Longhurst, P., Debattista, K., Gillibrand, R., and Chalmers, A. 2005. Analytic antialiasing for selective high fidelity rendering. In SIBGRAPI 2005. IEEE Computer Society Press, Los Alamitos. 359--366.
17. Longhurst, P., Debattista, K., and Chalmers, A. 2006. A gpu based saliency map for high-fidelity selective rendering. In AFRIGRAPH 2006 4th Int. Conf. on Computer Graphics, Virtual Reality, Visualisation and Interaction in Africa. ACM SIGGRAPH, 21--29.
18. Martens, W. and Myszkowski, K. 1998. Psychophysical validation of the visible differences predictor for global illumination applications. In Proceedings of IEEE Visualization '98. 18--23.
19. Mitchell, D. P. 1987. Generating antialiased images at low sampling densities. In SIGGRAPH '87: Proc. of the 14th Annual Conference on Computer Graphics and Interactive Techniques. ACM Press, New York. 65--72.
20. Myszkowski, K. 1998s. The visible differences predictor: Applications to global illumination problems. In Proc. of the Eurographics Workshop. 223--236.
21. Myszkowski, K. 2002. Perception-based global illumination, rendering, and animation techniques. In SCCG '02: Proc. of the 18th Spring Conference on Computer Graphics. ACM Press, New York. 13--24.
22. Narasimhan, S. G. and Nayar, S. K. 2003. Shedding light on the weather. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Vol. I. 665--672.
23. Neumann, D. and Gegenfurtner, K. R. 2002. Perception based image retrieval.
24. Prikryl, J. 2001. Radiosity methods driven by human perception. Ph.D. thesis, Institute of Computer Graphics and Algorithms, Vienna University of Technology.
25. Ramasubramanian, M., Pattanaik, S. N., and Greenberg, D. P. 1999. A perceptually based physical error metric for realistic image synthesis. In SIGGRAPH '99: Proc. of the 26th Annual Conference on Computer Graphics and Interactive Techniques. ACM Press/Addison-Wesley, New York. 73--82.
26. Rushmeier, H. 1994. Rendering participating media: Problems and solutions from application areas. In Proc. of the 5th Eurographics Workshop on Rendering. 117--126.
27. Siegel, R. and Howell, J. R. 1992. Thermal Radiation Heat Transfer. Hemisphere Publ., New York.
28. Stokes, W. A., Ferwerda, J. A., Walter, B., and Greenberg, D. P. 2004. Perceptual illumination components: A new approach to efficient, high quality global illumination rendering. ACM Trans. Graph. 23, 3, 742--749.
29. Sun, B., Ramamoorthi, R., Narasimhan, S. G., and Nayar, S. K. 2005. A practical analytic single scattering model for real time rendering. ACM Trans. Graph. 24, 3, 1040--1049.
30. Sundstedt, V., Debattista, K., and Chalmers, A. 2005a. Perceived aliasing thresholds in high-fidelity rendering. In APGV '05: Proceedings of the 2nd Symposium on Applied Perception in Graphics and Visualization. ACM Press, New York. 166--166.
31. Sundstedt, V., Debattista, K., Longhurst, P., Chalmers, A., and Troscianko, T. 2005b. Visual attention for efficient high-fidelity graphics. In Spring Conference on Computer Graphics (SCCG 2005). 162--168.
32. Tobii 2006. User Manual: Tobii Eye Tracker, ClearView Analysis Software. Tobii.
33. Woolley, C., Luebke, D., Watson, B., and Dayal, A. 2003. Interruptible rendering. In SI3D '03: Proceedings of the 2003 Symposium on Interactive 3D Graphics. ACM Press, New York. 143--151.
34. Yee, H., Pattanaik, S., and Greenberg, D. P. 2001. Spatiotemporal sensitivity and visual attention for efficient rendering of dynamic environments. ACM Trans. Graph. 20, 1, 39--65.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Image and video acquisition

        • 3D imaging

  • Computer graphics

    • Animation