A Position‐Free Path Integral for Homogeneous Slabs and Multiple Scattering on Smith Microfacets

Bitterli, Benedikt; d’Eon, Eugene

doi:10.1111/cgf.14589

Cited by 11 publications

(10 citation statements)

References 28 publications

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“…A current limitation of our model is that it does not handle multiple scattering among micrograins. To this end, recent solutions [Bitterli and d'Eon 2022;] could be followed, but they require the definition of the visible NDF, which we have not yet derived in our case. Another limitation is anisotropy.…”

Section: Discussionmentioning

confidence: 99%

“…Their elementary reflectance can be perfectly specular (through a Fresnel term in many cases) [Cook and Torrance 1982] or Lambertian [Oren and Nayar 1994]. The initial microfacet models are limited to single scattering but have been recently completed with multiple scattering effects either with numerical stochastic simulations for Smith [Bitterli and d'Eon 2022; or analytic models for v-grooves [Lee et al 2018;Xie and Hanrahan 2018]. Note that for now, multiple scattering is not considered in our porous layer and we leave this question to future work.…”

Section: Previous Workmentioning

confidence: 99%

See 1 more Smart Citation

A Micrograin BSDF Model for the Rendering of Porous Layers

Lucas,

Ribardiere,

Pacanowski

et al. 2023

SIGGRAPH Asia 2023 Conference Papers

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Section: Discussionmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

A Micrograin BSDF Model for the Rendering of Porous Layers

Lucas,

Ribardiere,

Pacanowski

et al. 2023

SIGGRAPH Asia 2023 Conference Papers

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“…Our approach focuses on coupling multiple physics in a single path space. The idea of coupling is precisely one of these interface questions that has recently emerged in both Computer Graphics (multiscale coupling [Bitterli and d'Eon 2022;Guo et al 2018;Heitz et al 2016;Wang et al 2022]) and Physics, in fields such as electromagnetic, solid physics, photochemistry Galtier et al 2016;Gattepaille et al 2018]. We believe that computer graphics and physics research would strongly benefit from a common theoretical framework to foster collaboration on that topic.…”

Section: Introductionmentioning

confidence: 99%

Coupling Conduction, Convection and Radiative Transfer in a Single Path-Space: Application to Infrared Rendering

Bati

Blanco

Coustet³

et al. 2023

ACM Trans. Graph.

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In the past decades, Monte Carlo methods have shown their ability to solve PDEs, independently of the dimensionality of the integration domain and for different use-cases (e.g. light transport, geometry processing, physics simulation). Specifically, the path-space formulation of transport equations is a key ingredient to define tractable and scalable solvers, and we observe nowadays a strong interest in the definition of simulation systems based on Monte Carlo algorithms. We also observe that, when simulating combined physics (e.g. thermal rendering from a heat transfer simulation), there is a lack of coupled Monte Carlo algorithms allowing to solve all the physics at once, in the same path space, rather than combining several independent MC estimators, a combination that would make the global solver critically sensitive to the complexity of each simulation space. This brings to our proposal: a coupled, single path-space, Monte Carlo algorithm for efficient multi-physics problems solving. In this work, we combine our understanding and knowledge of Physics and Computer Graphics to demonstrate how to formulate and arrange different simulation spaces into a single path space. We define a tractable formalism for coupled heat transfer simulation using Monte Carlo, and we leverage the path-space construction to interactively compute multiple simulations with different conditions in the same scene, in terms of boundary conditions and observation time. We validate our proposal in the context of infrared rendering with different thermal simulation scenarios: e.g., room temperature simulation, visualization of heat paths within materials (detection of thermal bridges), heat diffusion capacity of thermal exchanger. We expect that our theoretical framework will foster collaboration and multidisciplinary studies. The perspectives this framework opens are detailed and we suggest a research agenda towards the resolution of coupled PDEs at the interface of Physics and Computer Graphics.

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“…With this question in mind, many studies have already been proposed in the literature; going from numerical MC simulations to theoretical approaches [5][6][7][8] . Interestingly, this approach also applies to image rendering 9 .…”

Section: Introductionmentioning

confidence: 99%

Probability density function for random photon steps in a binary (isotropic-Poisson) statistical mixture

Binzoni¹,

Mazzolo²

2023

Preprint

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Monte Carlo (MC) simulations allowing to describe photons propagation in statistical mixtures represent an interest that goes way beyond the domain of optics, and can cover, e.g., nuclear reactor physics, image analysis or life science just to name a few. MC simulations are considered a "gold standard" because they give exact solutions (in the statistical sense), however, in the case of statistical mixtures they are enormously time consuming and their implementation is often extremely complex. For this reason, the aim of the present contribution is to propose a new approach that should allow us in the future to simplify the MC approach. This is done through an explanatory example, i.e.; by deriving the 'exact' analytical expression for the probability density function of photons' random steps (single step function, SSF) propagating in a medium represented as a binary (isotropic-Poisson) statistical mixture. The use of the SSF reduces the problem to an 'equivalent' homogeneous medium behaving exactly as the original binary statistical mixture. This will reduce hundreds time-consuming MC simulations to only one equivalent simple MC simulation. To the best of our knowledge the analytically 'exact' SSF for a binary (isotropic-Poisson) statistical mixture has never been derived before.

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A Position‐Free Path Integral for Homogeneous Slabs and Multiple Scattering on Smith Microfacets

Cited by 11 publications

References 28 publications

A Micrograin BSDF Model for the Rendering of Porous Layers

A Micrograin BSDF Model for the Rendering of Porous Layers

Coupling Conduction, Convection and Radiative Transfer in a Single Path-Space: Application to Infrared Rendering

Probability density function for random photon steps in a binary (isotropic-Poisson) statistical mixture

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