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BiDirectional Path Tracing
 PROCEEDINGS OF THIRD INTERNATIONAL CONFERENCE ON COMPUTATIONAL GRAPHICS AND VISUALIZATION TECHNIQUES (COMPUGRAPHICS ’93
, 1993
"... In this paper we present a new Monte Carlo rendering algorithm that seamlessly integrates the ideas of ..."
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Cited by 125 (10 self)
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In this paper we present a new Monte Carlo rendering algorithm that seamlessly integrates the ideas of
CoarseGrained Parallelism for Hierarchical Radiosity Using Group Iterative Methods
 Group Iterative Methods, Computer Graphics (SIGGRAPH 96
, 1996
"... This paper describes algorithms that allow multiple hierarchical radiosity solvers to work on the same radiosity solution in parallel. We have developed a system based on a group iterative approach that repeatedly: 1) partitions patches into groups, 2) distributes a copy of each group to a slave pro ..."
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Cited by 37 (3 self)
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This paper describes algorithms that allow multiple hierarchical radiosity solvers to work on the same radiosity solution in parallel. We have developed a system based on a group iterative approach that repeatedly: 1) partitions patches into groups, 2) distributes a copy of each group to a slave processor which updates radiosities for all patches in that group, and 3) merges the updates back into a master solution. The primary advantage of this approach is that separate instantiations of a hierarchical radiosity solver can gather radiosity to patches in separate groups in parallel with very little contention or communication overhead. This feature, along with automatic partitioning and dynamic load balancing algorithms, enables our implemented system to achieve significant speedups running on moderate numbers of workstations connected by a local area network. This system has been used to compute the radiosity solution for a very large model representing a five floor building with furni...
The use of global random directions to compute radiosity. Global Monte Carlo techniques.
, 1996
"... Contents Acknowledgements 3 Foreword 9 1 Introduction 11 2 PreviousWork 14 2.1 The Radiosity equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.1.1 Rendering Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.1.2 Rendering Equation for diffuse ..."
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Cited by 28 (16 self)
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Contents Acknowledgements 3 Foreword 9 1 Introduction 11 2 PreviousWork 14 2.1 The Radiosity equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.1.1 Rendering Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.1.2 Rendering Equation for diffuse surfaces . . . . . . . . . . . . . . . . . . . . 16 2.1.3 The Radiosity system of equations . . . . . . . . . . . . . . . . . . . . . . . 17 2.1.4 Two forms of the Form Factor integral . . . . . . . . . . . . . . . . . . . . . 18 2.1.5 The Form Factor integral as a contour integral . . . . . . . . . . . . . . . . 18 2.1.6 Differential area to area Form Factor . . . . . . . . . . . . . . . . . . . . . . 19 2.2 Computing the Form Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.2.1 Deterministic numerical solutions . . . . . . . . . . . . . . . . . . . . . . . . 22 2.3 Monte Carlo evaluation of the Form Factor integral . . . . . . . . . . . . . . . . .
An Information Theory Framework for the Analysis of Scene Complexity
, 1999
"... In this paper we present a new framework for the analysis of scene visibility and radiosity complexity. We introduce a number of complexity measures from information theory quantifying how difficult it is to compute with accuracy the visibility and radiosity in a scene. We define the continuous mu ..."
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Cited by 14 (8 self)
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In this paper we present a new framework for the analysis of scene visibility and radiosity complexity. We introduce a number of complexity measures from information theory quantifying how difficult it is to compute with accuracy the visibility and radiosity in a scene. We define the continuous mutual information as a complexity measure of a scene, independent of whatever discretisation, and discrete mutual information as the complexity of a discretised scene. Mutual information can be understood as the degree of correlation or dependence between all the points or patches of a scene. Thus, low complexity corresponds to low correlation and vice versa. Experiments illustrating that the best mesh of a given scene among a number of alternatives corresponds to the one with the highest discrete mutual information, indicate the feasibility of the approach. Unlike continuous mutual information, which is very cheap to compute, the computation of discrete mutual information can however b...
Animating radiosity environments through the MultiFrame Lighting Method
 Journal of Visualization and Computer Animation
, 2001
"... This paper presents the MultiFrame Lighting Method, an efficient algorithm to compute animations in radiosity environments. The method, based on global Monte Carlo techniques, performs the lighting simulation of groups of consecutive frames in a single process. All frames computed have the same ..."
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This paper presents the MultiFrame Lighting Method, an efficient algorithm to compute animations in radiosity environments. The method, based on global Monte Carlo techniques, performs the lighting simulation of groups of consecutive frames in a single process. All frames computed have the same accuracy as if they were computed independently while a significant high speedup is achieved. Results show that the method it is an interesting alternative for computing noninteractive radiosity animations for moderately complex scenarios. Copyright # 2001 John Wiley & Sons, Ltd
Entropy of Scene Visibility
, 1999
"... We propose a new approach, based on information theory, to study the visibility of a scene. Thus, we will define the concepts of entropy and mutual information applied to 3D scene visibility. Mainly, we analize the concept of entropy (or randomness) of scene visibility and we examine the relationshi ..."
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Cited by 4 (3 self)
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We propose a new approach, based on information theory, to study the visibility of a scene. Thus, we will define the concepts of entropy and mutual information applied to 3D scene visibility. Mainly, we analize the concept of entropy (or randomness) of scene visibility and we examine the relationship between entropy of scene visibility and the expected value of the mean square error for all form factors. Next, these concepts are applied to diverse sample scenes and the accuracy of the values presented is analyzed. Key Words: Rendering, Radiosity, Monte Carlo, Information Theory, Entropy 1 Introduction In this paper, the visibility of a scene, which is directly related to form factors [1], is analyzed from the viewpoint of information theory. In many different fields, the concept of entropy has been studied at length and has been used as a starting point in order to study complexity [6, 10, 18, 19]. In our case, we study the entropy of scene visibility and leave the study of scene com...
Scene Continuous Mutual Information as Least Upper Bound of Discrete One
, 1999
"... In this report we define the continuous mutual information of scene visibility, independent of whatever discretisation, and we prove that it is the least upper bound of the discrete mutual information. Thus, continuous mutual information can be understood as the maximum information transfer in a sce ..."
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Cited by 2 (2 self)
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In this report we define the continuous mutual information of scene visibility, independent of whatever discretisation, and we prove that it is the least upper bound of the discrete mutual information. Thus, continuous mutual information can be understood as the maximum information transfer in a scene. Keywords: rendering, radiosity, Monte Carlo, information theory, entropy, mutual information 1. Previous concepts 1.1. Radiosity and form factor The radiosity equation solves for the illumination in a diffuse environment. It can be written in the form B(x) = E(x) +R(x) Z S B(x 0 )V (x; x 0 ) cosqcosq 0 pr 2 dA 0 (1) where B(x) is the radiosity, E(x) is the emittance, R(x) is the reflectance, S is the set of surfaces that form the environment, x; x 0 are points on surfaces of the environment, dA 0 is an area differential at point x 0 , r is the distance between x and x 0 , V (x; x 0 ) is a visibility function equal to 1 if x and x 0 are mutually visible and ...
An InformationTheory Framework for the Study of the Complexity of Visibility and Radiosity in a Scene
, 2002
"... this dissertation. 1.1 Radiosity, Complexity, and Information Theory The three fundamental pillars of this thesis are radiosity, complexity, and information theory: One of the most important topics in computer graphics is the accurate computation of the global illumination in a closed virtual ..."
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this dissertation. 1.1 Radiosity, Complexity, and Information Theory The three fundamental pillars of this thesis are radiosity, complexity, and information theory: One of the most important topics in computer graphics is the accurate computation of the global illumination in a closed virtual environment (scene), i.e. the intensities of light over all its surfaces. "The production of realistic images requires in particular a precise treatment of lighting e#ects that can be achieved by simulating the underlying physical phenomena of light emission, propagation, and reflection"[82]. This type of simulation is called global illumination and is represented by the rendering equation [43], which is a Fredholm integral equation of the second kind. However obtaining an exact representation of the illumination is an intractable problem. Many di#erent techniques are used to obtain an approximate quantification of it [12, 82, 33]
Random Walk Radiosity with generalized transition probabilities
 Research Report IIiA–98– 07–RR, Institut d’Informàtica i Aplicacions, Universitat de
, 1998
"... In this paper we study random walk estimators for radiosity with generalized transition and absorption probabilities. That is, a path will travel from patch to patch according to an arbitrary transition probability, and survive or be absorbed in it according to another arbitrary absorption probabili ..."
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Cited by 2 (1 self)
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In this paper we study random walk estimators for radiosity with generalized transition and absorption probabilities. That is, a path will travel from patch to patch according to an arbitrary transition probability, and survive or be absorbed in it according to another arbitrary absorption probability. The estimators studied so far, those with arbitrary absorption probabilities but with the Form Factors as transition probabilities, are obviously a particular case of the more general case presented here. Practical applications of random walks with generalized probabilities are given. Closed forms for the variances are found, together with necessary and sufficient conditions for their existence. The variances are shown to fulfill a system of equations, which is a classical result by Halton. Some particular cases are studied, including null variance estimators, which represent the optimal case. Keywords: Radiosity, Monte Carlo, Random Walk, Variance 1 Introduction Discrete or continuous...
Comparing Finite and Biased Infinite Path Length Shooting Random Walk Estimators for Radiosity
, 1997
"... . In this paper we compare the best shooting random walk estimator with expected finite path length and the estimator resulting of biasing the infinite one. Heuristic formulae for the Mean Square Error of both estimators are given, and based on them a formula for the relative efficiency of both esti ..."
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. In this paper we compare the best shooting random walk estimator with expected finite path length and the estimator resulting of biasing the infinite one. Heuristic formulae for the Mean Square Error of both estimators are given, and based on them a formula for the relative efficiency of both estimators is presented. The results are contrasted with different tests. The formulae for the MSE are also useful to know a priori the number of paths (or particles) needed to obtain a given error. Keywords: Rendering, Radiosity, Monte Carlo, Random Walk. 1 Introduction Shooting random walk radiosity proceeds by sending rays (or particles, or paths) from the sources which travel through the scene according to the Form Factors transition probabilities, either discrete patchtopatch or continuous pointtopoint Form Factors. On each bounce, the exit point can be the same impinging point, as in nondiscrete methods [2], [4], [12] and Particle Tracing [5], or can be take at random on the patch [7...