Photon differentials
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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Photon differentials. / Schjøth, Lars; Revall Frisvad, Jeppe; Erleben, Kenny; Sporring, Jon.
GRAPHITE 2007: Proceedingsof the 5th international conference on computer graphics and interactive techniques in Australia and Southeast Asia, December 1-4, 2007, Perth, Western Austalia. Association for Computing Machinery, 2007. p. 179-186.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Photon differentials
AU - Schjøth, Lars
AU - Revall Frisvad, Jeppe
AU - Erleben, Kenny
AU - Sporring, Jon
N1 - Conference code: 5
PY - 2007
Y1 - 2007
N2 - A number of popular global illumination algorithms uses density estimation to approximate indirect illumination. The density estimate is performed on finite points -- particles -- generated by a stochastic sampling of the scene. In the course of the sampling, particles, representing light, are stochastically emitted from the light sources and reflected around the scene. The sampling induces noise, which in turn is handled by the density estimate during the illumination reconstruction. Unfortunately, this noise reduction imposes a systematic error (bias), which is seen as a blurring of prominent illumination features. This is often not desirable as these may lose clarity or vanish altogether.We present an accurate method for reconstruction of indirect illumination with photon mapping. Instead of reconstructing illumination using classic density estimation on finite points, we use the correlation of light footprints, created by using Ray Differentials during the light pass. This procedure gives a high illumination accuracy, improving the trade-off between bias and variance considerable as compared to traditional particle tracing algorithms. In this way we preserve structures in indirect illumination.
AB - A number of popular global illumination algorithms uses density estimation to approximate indirect illumination. The density estimate is performed on finite points -- particles -- generated by a stochastic sampling of the scene. In the course of the sampling, particles, representing light, are stochastically emitted from the light sources and reflected around the scene. The sampling induces noise, which in turn is handled by the density estimate during the illumination reconstruction. Unfortunately, this noise reduction imposes a systematic error (bias), which is seen as a blurring of prominent illumination features. This is often not desirable as these may lose clarity or vanish altogether.We present an accurate method for reconstruction of indirect illumination with photon mapping. Instead of reconstructing illumination using classic density estimation on finite points, we use the correlation of light footprints, created by using Ray Differentials during the light pass. This procedure gives a high illumination accuracy, improving the trade-off between bias and variance considerable as compared to traditional particle tracing algorithms. In this way we preserve structures in indirect illumination.
KW - Faculty of Science
KW - Global belysning
KW - Photon mapping
KW - Ray tracing
KW - Partikel sporing
KW - Ray differentials
KW - Global Illumination
KW - Photon mapping
KW - Ray tracing
KW - Particle tracing
KW - Ray differentials
M3 - Article in proceedings
SN - 978-1-59593-912-8
SP - 179
EP - 186
BT - GRAPHITE 2007
PB - Association for Computing Machinery
Y2 - 1 December 2007 through 4 December 2007
ER -
ID: 1948442