No Access

A NEW COMPUTATIONAL WAY TO MONTE CARLO GLOBAL ILLUMINATION

QING XU

Department of Computer Science and Technology, Tianjin University, Tianjin 300072, China

Search for more papers by this author

WEI WANG

Department of Computer Science and Technology, Tianjin University, Tianjin 300072, China

Search for more papers by this author

, and

SHIQIANG BAO

Department of Computer Science and Technology, Tianjin University, Tianjin 300072, China

Search for more papers by this author

https://doi.org/10.1142/S0219467806002057Cited by:1 (Source: Crossref)

Abstract

In this paper, we present a new Monte Carlo computational way for solving the global illumination problem whereby plenty of unbiased estimators can be employed to enrich the solutions leading to simple error control and faster estimation. Especially so, the zero variance importance sampling procedure can be exploited to calculate the global illumination optimally. Based on the new scheme, a new Monte Carlo global illumination algorithm and its importance driven version have been developed and carried out. Results, which have been obtained by rendering test scenes, show that this new framework is promising.

Keywords:

Remember to check out the Check out our Most Cited Articles!
Check out these titles on Image Analysis

References

P. Bekaert, PhD Thesis, Katholieke Universiteit Leuven, Belgium (1999) . Google Scholar
J. T. Kajiya, Computer Graphics 20, 143 (1986). Crossref, Google Scholar
S. N. Pattanaik and S. P. Mudur, Computer Graphics Forum 12, 131 (1993). Crossref, Google Scholar
S. N. Pattanaik and S. P. Mudur, ACM Transactions on Graphics 14, 77 (1995). Crossref, Web of Science, Google Scholar
J. Arvo, Linear operators and integral equations in global illumination, SIGGRAPH '93 Course Notes42 (ACM Press, New York, 1993) p. 2. Google Scholar
R. Y. Rubinstein, Simulation and the Monte Carlo Method (John Wiley & Sons, New York, 1981) p. 173. Crossref, Google Scholar
S. N. Pattanaik and S. P. Mudur, Computers & Graphics 17, 387 (1993). Crossref, Web of Science, Google Scholar
L. Szirmay-Kalos, Proc. of Spring Conference on Computer Graphics '99, ed. Jiri Zara (Commenius, Slovakia, 1999) p. 3. Google Scholar
H. W. Jensen, Rendering Techniques '95, eds. P. Harahan and W. Purgathofer (Springer-Verlag, Vienna, 1995) p. 326. Google Scholar
E. P. Lafortune and Y. D. Willems, Rendering Techniques '95, eds. P. Harahan and W. Purgathofer (Springer-Verlag, Vienna, 1995) p. 11. Google Scholar
L. Szirmay-Kalos, C. Balázs and W. Purgathofer, Computers & Graphics 23, 203 (1999). Crossref, Web of Science, Google Scholar
J. Spanier, Monte-Carlo and Quasi-Monte Carlo Methods in Scientific Computing 1994, eds. H. Niederreiter and P. Shiue (Springer-Verlag, New York, 1995) p. 121. Crossref, Google Scholar
J. Spanier , Monte Carlo and Quasi-Monte Carlo Methods 1996 , eds. H. Niederreiter et al. ( Springer-Verlag , New York , 1998 ) . Google Scholar
L. Li and J. Spanier, Monte Carlo Methods and Applications 3, 171 (1997). Google Scholar
R. R. Coveyou, V. R. Cain and K. J. Yost, Nuclear Science and Engineering 27, 219 (1967). Crossref, Web of Science, Google Scholar
D. B. MacMillan, Nuclear Science and Engineering 26, 366 (1966). Crossref, Web of Science, Google Scholar
K. Bouatouch, S. N. Pattanaik and E. Zeghers, Computer Graphics Forum 15, C327 (1996). Crossref, Google Scholar
E. P. Lafortune and Y. D. Willems, Using the Modified Phong BRDF for Physically Based Rendering, Department of Computer Science, K. U. Leuven, November (1994) Report CW197 . Google Scholar
L. Szirmay-Kalos, Monte-Carlo Methods in Global Illumination, Institute of Computer Graphics, Vienna University of Technology (October 1999), Script . Google Scholar
M. D. McCool, ACM Transactions on Graphics 2, 171 (1999). Google Scholar
E. Veach and L. Guibas, Proc. Eurographics Workshop on Rendering 1994, eds. G. Sakas, P. Shirley and E. Muller (Springer-Verlag, Berlin, 1995) p. 147. Google Scholar