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Metropolis Light Transport for Participating Media
Mark Pauly Thomas Kollig Alexander Keller ETH Zürich University of Kaiserslautern
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Overview Light Transport for Participating Media
Path Integral Formulation Sampling Rendering with Metropolis Light Transport Results Conclusions
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Related Work FE Methods MC Methods Light Tracing ‘93 Zonal Methods ‘87
Rushmeier, Torrance Light Tracing ‘93 Pattanaik, Mudur Hierarchical Radiosity ‘93 Bhate Bidirectional Path Tracing ‘96 Lafortune, Willems Spherical Harmonics ‘84 Kajiya, von Herzen Photon Map ‘98 Jensen, Christensen Discrete Ordinates ‘94 Languenou, Bouatouch, Chelle Metropolis Light Transport ‘97 Veach, Guibas
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Light Transport Global Balance Equation In-scattering Streaming
Emission Absorption Out-scattering
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Path Integral Formulation
Measurement Equation Path Integral
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Path Characteristic sensor medium object light source 1 1 1
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Path Space Path Space Measure
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Measurement Contribution Function
Path Integral
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Sampling Line Integral Computation: Ray Marching Equidistant Sampling
efficient aliasing Stratified Sampling anti-aliasing inefficient Random Offset Sampling
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Metropolis Light Transport
Generate a random walk through path space For each path deposit a constant amount of energy at the corresponding pixel Obtain desired image by distributing paths according to image contribution Metropolis sampling
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Metropolis Sampling Propose a mutation of current path
Compute acceptance probability Choose as new sample if Samples are correlated we can exploit coherence
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Mutation Strategies Bidirectional Mutations Perturbations
large changes to the current path ensures ergodicity Perturbations high acceptance probability changes to image location low cost Scattering Perturbations Propagation Perturbations Sensor Perturbations Caustic Perturbations
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Propagation Perturbation
medium image plane light source eye
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Results
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Results
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Results
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Conclusions Participating media are fully integrated
inhomogeneous media multiple, anisotropic scattering volume caustics color bleeding General geometry and reflection models Robust Complex Scenes Difficult Lighting Situations
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