SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
A ray tracing method for illumination calculation in diffuse-specular scenes
Proceedings on Graphics interface '90
A framework for the analysis of error in global illumination algorithms
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
The RADIANCE lighting simulation and rendering system
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Optimally combining sampling techniques for Monte Carlo rendering
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
A ray tracing solution for diffuse interreflection
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Ray Shooting, Depth Orders and Hidden Surface Removal
Ray Shooting, Depth Orders and Hidden Surface Removal
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Accelerating path tracing by re-using paths
EGRW '02 Proceedings of the 13th Eurographics workshop on Rendering
Adaptive sampling for environment mapping
Proceedings of the 26th Spring Conference on Computer Graphics
Gathering for free in random walk radiosity
EGWR'99 Proceedings of the 10th Eurographics conference on Rendering
Parallel Monte Carlo radiosity using scene partitioning
International Journal of High Performance Computing Applications
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In this paper, we study the error and complexity of the discrete random walk Monte Carlo technique for Radiosity, both the shooting and gathering methods. We show that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. We give and compare three unbiased estimators for each method, and obtain closed forms and bounds for their variances. We also bound the expected value of the Mean Square Error (MSE). Some of the results obtained are also shown to be valid for the nondiscrete gathering case. We also give bounds for the variances and MSE for the infinite path length estimators; these bounds might be useful in the study of the biased estimators resulting of cutting off the infinite path.