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173
Metropolis Light Transport
 Computer Graphics (SIGGRAPH '97 Proceedings
, 1997
"... We present a new Monte Carlo method for solving the light transport problem, inspired by the Metropolis sampling method in computational physics. To render an image, we generate a sequence of light transport paths by randomly mutating a single current path (e.g. adding a new vertex to the path). Eac ..."
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Cited by 203 (1 self)
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We present a new Monte Carlo method for solving the light transport problem, inspired by the Metropolis sampling method in computational physics. To render an image, we generate a sequence of light transport paths by randomly mutating a single current path (e.g. adding a new vertex to the path). Each mutation is accepted or rejected with a carefully chosen probability, to ensure that paths are sampled according to the contribution they make to the ideal image. We then estimate this image by sampling many paths, and recording their locations on the image plane. Our algorithm is unbiased, handles general geometric and scattering models, uses little storage, and can be orders of magnitude more e#cient than previous unbiased approaches. It performs especially well on problems that are usually considered di#cult, e.g. those involving bright indirect light, small geometric holes, or glossy surfaces. Furthermore, it is competitive with previous unbiased algorithms even for relatively simple ...
The bridge test for sampling narrow passages with probabilistic roadmap planners
 IN PROC. IEEE INT. CONF. ON ROBOTICS & AUTOMATION
, 2003
"... Probabilistic roadmap (PRM) planners have been successful in path planning of robots with many degrees of freedom, but narrow passages in a robot’s configuration space create significant difficulty for PRM planners. This paper presents a hybrid sampling strategy in the PRM framework for finding pat ..."
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Cited by 120 (6 self)
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Probabilistic roadmap (PRM) planners have been successful in path planning of robots with many degrees of freedom, but narrow passages in a robot’s configuration space create significant difficulty for PRM planners. This paper presents a hybrid sampling strategy in the PRM framework for finding paths through narrow passages. A key ingredient of the new strategy is the bridge test, which boosts the sampling density inside narrow passages. The bridge test relies on simple tests of local geometry and can be implemented efficiently in highdimensional configuration spaces. The strengths of the bridge test and uniform sampling complement each other naturally and are combined to generate the final hybrid sampling strategy. Our planner was tested on point robots and articulated robots in planar workspaces. Preliminary experiments show that the hybrid sampling strategy enables relatively small roadmaps to reliably capture the connectivity of configuration spaces with difficult narrow passages.
Structured Importance Sampling of Environment Maps
, 2003
"... We introduce structured importance sampling, a new technique for efficiently rendering scenes illuminated by distant natural illumination given in an environment map. Our method handles occlusion, highfrequency lighting, and is significantly faster than alternative methods based on Monte Carlo samp ..."
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Cited by 102 (9 self)
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We introduce structured importance sampling, a new technique for efficiently rendering scenes illuminated by distant natural illumination given in an environment map. Our method handles occlusion, highfrequency lighting, and is significantly faster than alternative methods based on Monte Carlo sampling. We achieve this speedup as a result of several ideas. First, we present a new metric for stratifying and sampling an environment map taking into account both the illumination intensity as well as the expected variance due to occlusion within the scene. We then present a novel hierarchical stratification algorithm that uses our metric to automatically stratify the environment map into regular strata. This approach enables a number of rendering optimizations, such as preintegrating the illumination within each stratum to eliminate noise at the cost of adding bias, and sorting the strata to reduce the number of sample rays. We have rendered several scenes illuminated by natural lighting, and our results indicate that structured importance sampling is better than the best previous Monte Carlo techniques, requiring one to two orders of magnitude fewer samples for the same image quality.
A Random Sampling Scheme for Path Planning
 INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
, 1996
"... Several randomizod path planners have been proposed during the last few years. Their attractiveness stems from their applicability to virtually any type of robots, and their empirically observed success. In this paper we attempt to present a unifying view of these planners and to theoretically expla ..."
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Cited by 101 (22 self)
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Several randomizod path planners have been proposed during the last few years. Their attractiveness stems from their applicability to virtually any type of robots, and their empirically observed success. In this paper we attempt to present a unifying view of these planners and to theoretically explain their success. First, we introduce a general planning scheme that consists of randomly sampling the robot' s configuration space. We then describe two previously developed planners as instances of planners based on this scheme, but applying very different sampling strategies. These planners are probabilistically complete: if a path exists, they will find one with high probability, if we let them run long enough. Next, for one of the planners, we analyze the relation between the probability of failure and the running time. Under assumptions characterizing the "goodness" of the robot's free space, we show that the running time only grows as the absolute value of the logarithm of the probability of failure that we are willing to tolerate. We also show that it increases at a reasonable rate as the space goodness degrades. In the last section we suggest directions for future research.
Progressive photon mapping
 ACM Transactions on Graphics (SIGGRAPH Asia Proceedings
, 2008
"... Figure 1: Tools with a flashlight. The scene is illuminated by caustics from the flashlight, which cause SDS paths on the flashlight and highly glossy reflections of caustics on the bolts and plier. The flashlight and the plier are out of focus. Using the same rendering time, our method (right) robu ..."
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Cited by 68 (7 self)
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Figure 1: Tools with a flashlight. The scene is illuminated by caustics from the flashlight, which cause SDS paths on the flashlight and highly glossy reflections of caustics on the bolts and plier. The flashlight and the plier are out of focus. Using the same rendering time, our method (right) robustly renders the combination of the complex illumination setting and the distributed ray tracing effects where progressive photon mapping is inefficient (left). This paper presents a simple extension of progressive photon mapping for simulating global illumination with effects such as depthoffield, motion blur, and glossy reflections. Progressive photon mapping is a robust global illumination algorithm that can handle complex illumination settings including speculardiffusespecular paths. The algorithm can compute the correct radiance value at a point in the limit. However, progressive photon mapping is not effective at rendering distributed ray tracing effects, such as depthoffield, that requires multiple pixel samples in order to compute the correct average radiance value over a region. In this paper, we introduce a new formulation of progressive photon mapping, called stochastic progressive photon mapping, which makes it possible to compute the correct average radiance value for a region. The key idea is to use shared photon statistics within the region rather than isolated photon statistics at a point. The algorithm is easy to implement, and our results demonstrate how it efficiently handles scenes with distributed ray tracing effects, while maintaining the robustness of progressive photon mapping in scenes with complex lighting.
Monte Carlo Evaluation Of NonLinear Scattering Equations For Subsurface Reflection
"... We describe a new mathematical framework for solving a wide variety of rendering problems based on a nonlinear integral scattering equation. This framework treats the scattering functions of complex aggregate objects as firstclass rendering primitives; these scattering functions accurately account ..."
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Cited by 61 (3 self)
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We describe a new mathematical framework for solving a wide variety of rendering problems based on a nonlinear integral scattering equation. This framework treats the scattering functions of complex aggregate objects as firstclass rendering primitives; these scattering functions accurately account for all scattering events inside them. We also describe new techniques for computing scattering functions from the composition of scattering objects. We demonstrate that solution techniques based on this new approach can be more efficient than previous techniques based on radiance transport and the equation of transfer and we apply these techniques to a number of problems in rendering scattering from complex surfaces.
Rendering Participating Media with Bidirectional Path Tracing
 In Eurographics Rendering Workshop
, 1996
"... In this paper we show how bidirectional path tracing can be extended to handle global illumination effects due to participating media. The resulting imagebased algorithm is computationally expensive but more versatile than previous solutions. It correctly handles multiple scattering in nonhomog ..."
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Cited by 59 (0 self)
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In this paper we show how bidirectional path tracing can be extended to handle global illumination effects due to participating media. The resulting imagebased algorithm is computationally expensive but more versatile than previous solutions. It correctly handles multiple scattering in nonhomogeneous, anisotropic media in complex illumination situations. We illustrate its specific advantages by means of examples.
Mathematical Models and Monte Carlo Algorithms for Physically Based Rendering
, 1996
"... Algorithms for image synthesis render photorealistic imagery, given the description of a scene. Physically based rendering specifically stresses the physical correctness of the algorithms and their results. The algorithms perform an accurate simulation of the behaviour of light, in order to faithfu ..."
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Cited by 46 (1 self)
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Algorithms for image synthesis render photorealistic imagery, given the description of a scene. Physically based rendering specifically stresses the physical correctness of the algorithms and their results. The algorithms perform an accurate simulation of the behaviour of light, in order to faithfully render global illumination effects such as soft shadows, glossy reflections and indirect illumination. In this dissertation we investigate imagebased Monte Carlo rendering algorithms. We pay special attention to their correctness, their versatility and their efficiency. First of all, we discuss theoretical frameworks that describe the global illumination problem. These formal mathematical models are the first step to ensure the correctness of the eventual results. Moreover, they allow to apply standard numerical techniques to compute a solution. We give an overview of existing models, which are based on the rendering equation and the potential equation. We then introduce a model based ...