Monte Carlo Methods for Volumetric Light Transport Simulation

Novák, Jan; Georgiev, Iliyan; Hanika, Johannes; Jarosz, Wojciech

doi:10.1111/cgf.13383

Cited by 107 publications

(116 citation statements)

References 131 publications

(139 reference statements)

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“…However, while they use NCAs in acceleration grids, they do not achieve insensitivity of computing times to the resolution of the volumetric data. With distinct applicative objectives, strong efforts have also been made by the film industry, especially by Disney Research, which revisited NCAs and transformed them into a validated industrial practice (Kutz et al, ; Novák et al, , ).…”

Section: Acceleration Grids For Large Surface and Volume Data Setsmentioning

confidence: 99%

“…Among the first consequences of the analysis of NCAs in their integral forms is the fact that acceleration grids could indeed be introduced for volumes (Iwabuchi & Okamura, ; Kutz et al, ; Novák et al, ). Such structures are expected to ensure fast traversal of the

\overset{k}{true}

‐field used in NCAs, and fast access to the true k value when a collision is found in the transformed field, all the while minimizing the computational cost of handling null collisions by locally adjusting the

\overset{k}{true}

‐field to the true k field.…”

Section: Acceleration Grids For Large Surface and Volume Data Setsmentioning

confidence: 99%

See 1 more Smart Citation

A Path‐Tracing Monte Carlo Library for 3‐D Radiative Transfer in Highly Resolved Cloudy Atmospheres

Villefranque

Fournier

Couvreux

et al. 2019

J Adv Model Earth Syst

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Interactions between clouds and radiation are at the root of many difficulties in numerically predicting future weather and climate and in retrieving the state of the atmosphere from remote sensing observations. The broad range of issues related to these interactions, and to three‐dimensional interactions in particular, has motivated the development of accurate radiative tools able to compute all types of radiative metrics, from monochromatic, local, and directional observables to integrated energetic quantities. Building on this community effort, we present here an open‐source library for general use in Monte Carlo algorithms. This library is devoted to the acceleration of ray tracing in complex data, typically high‐resolution large‐domain grounds and clouds. The main algorithmic advances embedded in the library are related to the construction and traversal of hierarchical grids accelerating the tracing of paths through heterogeneous fields in null‐collision (maximum cross‐section) algorithms. We show that with these hierarchical grids, the computing time is only weakly sensitive to the refinement of the volumetric data. The library is tested with a rendering algorithm that produces synthetic images of cloud radiances. Other examples of implementation are provided to demonstrate potential uses of the library in the context of 3‐D radiation studies and parameterization development, evaluation, and tuning.

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Section: Acceleration Grids For Large Surface and Volume Data Setsmentioning

confidence: 99%

\overset{k}{true}

\overset{k}{true}

‐field to the true k field.…”

Section: Acceleration Grids For Large Surface and Volume Data Setsmentioning

confidence: 99%

A Path‐Tracing Monte Carlo Library for 3‐D Radiative Transfer in Highly Resolved Cloudy Atmospheres

Villefranque

Fournier

Couvreux

et al. 2019

J Adv Model Earth Syst

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show abstract

“…Here, we focus on works related directly with the scope of the paper. For a wider overview on the field, we refer to the recent survey by Novák et al [NGHJ18]. Jensen and Christensen [JC98] were the first to extend photon mapping to media, and Jarosz and colleagues [JZJ08] significantly improved its efficiency with the beam radiance estimate, which replaces repeated point queries with one 'beam' query finding all photons along the entire camera ray.…”

Section: Related Workmentioning

confidence: 99%

Progressive Transient Photon Beams

Marco

Guillén

Jarosz

et al. 2019

Computer Graphics Forum

Self Cite

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In this work, we introduce a novel algorithm for transient rendering in participating media. Our method is consistent, robust and is able to generate animations of time‐resolved light transport featuring complex caustic light paths in media. We base our method on the observation that the spatial continuity provides an increased coverage of the temporal domain, and generalize photon beams to transient‐state. We extend stead‐state photon beam radiance estimates to include the temporal domain. Then, we develop a progressive variant of our approach which provably converges to the correct solution using finite memory by averaging independent realizations of the estimates with progressively reduced kernel bandwidths. We derive the optimal convergence rates accounting for space and time kernels, and demonstrate our method against previous consistent transient rendering methods for participating media.

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“…In recent work, even deep learning techniques were applied to support volume rendering [KMM * 17]. For a thorough overview on most recent techniques, see [NGHJ18].…”

Section: Previous Workmentioning

confidence: 99%

Adaptive Temporal Sampling for Volumetric Path Tracing of Medical Data

Martschinke

Hartnagel

Keinert

et al. 2019

Computer Graphics Forum

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Monte‐Carlo path tracing techniques can generate stunning visualizations of medical volumetric data. In a clinical context, such renderings turned out to be valuable for communication, education, and diagnosis. Because a large number of computationally expensive lighting samples is required to converge to a smooth result, progressive rendering is the only option for interactive settings: Low‐sampled, noisy images are shown while the user explores the data, and as soon as the camera is at rest the view is progressively refined. During interaction, the visual quality is low, which strongly impedes the user's experience. Even worse, when a data set is explored in virtual reality, the camera is never at rest, leading to constantly low image quality and strong flickering. In this work we present an approach to bring volumetric Monte‐Carlo path tracing to the interactive domain by reusing samples over time. To this end, we transfer the idea of temporal antialiasing from surface rendering to volume rendering. We show how to reproject volumetric ray samples even though they cannot be pinned to a particular 3D position, present an improved weighting scheme that makes longer history trails possible, and define an error accumulation method that downweights less appropriate older samples. Furthermore, we exploit reprojection information to adaptively determine the number of newly generated path tracing samples for each individual pixel. Our approach is designed for static, medical data with both volumetric and surface‐like structures. It achieves good‐quality volumetric Monte‐Carlo renderings with only little noise, and is also usable in a VR context.

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Monte Carlo Methods for Volumetric Light Transport Simulation

Cited by 107 publications

References 131 publications

A Path‐Tracing Monte Carlo Library for 3‐D Radiative Transfer in Highly Resolved Cloudy Atmospheres

A Path‐Tracing Monte Carlo Library for 3‐D Radiative Transfer in Highly Resolved Cloudy Atmospheres

Progressive Transient Photon Beams

Adaptive Temporal Sampling for Volumetric Path Tracing of Medical Data

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