Quantifying the Error of Light Transport Algorithms

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Quantifying the Error of Light Transport Algorithms. / Celarek, A.; Jakob, W.; Wimmer, M.; Lehtinen, J.

julkaisussa: Computer Graphics Forum, Vuosikerta 38, Nro 4, 01.07.2019, s. 111-121.

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

Harvard

Celarek, A, Jakob, W, Wimmer, M & Lehtinen, J 2019, 'Quantifying the Error of Light Transport Algorithms', Computer Graphics Forum, Vuosikerta. 38, Nro 4, Sivut 111-121. https://doi.org/10.1111/cgf.13775

APA

Vancouver

Author

Celarek, A. ; Jakob, W. ; Wimmer, M. ; Lehtinen, J. / Quantifying the Error of Light Transport Algorithms. Julkaisussa: Computer Graphics Forum. 2019 ; Vuosikerta 38, Nro 4. Sivut 111-121.

Bibtex - Lataa

@article{2f6e32148a344911a800c6300b47f69f,
title = "Quantifying the Error of Light Transport Algorithms",
abstract = "This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two-fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per-pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per-pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.",
keywords = "CCS Concepts, • Computing methodologies → Ray tracing",
author = "A. Celarek and W. Jakob and M. Wimmer and J. Lehtinen",
year = "2019",
month = "7",
day = "1",
doi = "10.1111/cgf.13775",
language = "English",
volume = "38",
pages = "111--121",
journal = "Computer Graphics Forum",
issn = "0167-7055",
publisher = "WILEY-BLACKWELL",
number = "4",

}

RIS - Lataa

TY - JOUR

T1 - Quantifying the Error of Light Transport Algorithms

AU - Celarek, A.

AU - Jakob, W.

AU - Wimmer, M.

AU - Lehtinen, J.

PY - 2019/7/1

Y1 - 2019/7/1

N2 - This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two-fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per-pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per-pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.

AB - This paper proposes a new methodology for measuring the error of unbiased physically based rendering algorithms. The current state of the art includes mean squared error (MSE) based metrics and visual comparisons of equal-time renderings of competing algorithms. Neither is satisfying as MSE does not describe behavior and can exhibit significant variance, and visual comparisons are inherently subjective. Our contribution is two-fold: First, we propose to compute many short renderings instead of a single long run and use the short renderings to estimate MSE expectation and variance as well as per-pixel standard deviation. An algorithm that achieves good results in most runs, but with occasional outliers is essentially unreliable, which we wish to quantify numerically. We use per-pixel standard deviation to identify problematic lighting effects of rendering algorithms. The second contribution is the error spectrum ensemble (ESE), a tool for measuring the distribution of error over frequencies. The ESE serves two purposes: It reveals correlation between pixels and can be used to detect outliers, which offset the amount of error substantially.

KW - CCS Concepts

KW - • Computing methodologies → Ray tracing

UR - http://www.scopus.com/inward/record.url?scp=85070100686&partnerID=8YFLogxK

U2 - 10.1111/cgf.13775

DO - 10.1111/cgf.13775

M3 - Article

AN - SCOPUS:85070100686

VL - 38

SP - 111

EP - 121

JO - Computer Graphics Forum

JF - Computer Graphics Forum

SN - 0167-7055

IS - 4

ER -

ID: 38732156