| 000 | 03839nam a22005295i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-79567-1 | ||
| 003 | DE-He213 | ||
| 005 | 20240730164306.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 220601s2015 sz | s |||| 0|eng d | ||
| 020 |
_a9783031795671 _9978-3-031-79567-1 |
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| 024 | 7 |
_a10.1007/978-3-031-79567-1 _2doi |
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_a510 _223 |
| 100 | 1 |
_aMarques, Ricardo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983584 |
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| 245 | 1 | 0 |
_aEfficient Quadrature Rules for Illumination Integrals _h[electronic resource] : _bFrom Quasi Monte Carlo to Bayesian Monte Carlo / _cby Ricardo Marques, Christian Bouville, Luís Paulo Santos, Kadi Bouatouch. |
| 250 | _a1st ed. 2015. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015. |
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| 300 |
_aX, 82 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSynthesis Lectures on Computer Graphics and Animation, _x1933-9003 |
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| 505 | 0 | _aIntroduction -- Spherical Fibonacci Point Sets for QMC Estimates of Illumination Integrals -- Bayesian Monte Carlo for Global Illumination -- Bibliography -- Authors' Biographies. | |
| 520 | _aRendering photorealistic images is a costly process which can take up to several days in the case of high quality images. In most cases, the task of sampling the incident radiance function to evaluate the illumination integral is responsible for an important share of the computation time. Therefore, to reach acceptable rendering times, the illumination integral must be evaluated using a limited set of samples. Such a restriction raises the question of how to obtain the most accurate approximation possible with such a limited set of samples. One must thus ensure that sampling produces the highest amount of information possible by carefully placing and weighting the limited set of samples. Furthermore, the integral evaluation should take into account not only the information brought by sampling but also possible information available prior to sampling, such as the integrand smoothness. This idea of sparse information and the need to fully exploit the little information available is present throughout this book. The presented methods correspond to the state-of-the-art solutions in computer graphics, and take into account information which had so far been underexploited (or even neglected) by the previous approaches. The intended audiences are Ph.D. students and researchers in the field of realistic image synthesis or global illumination algorithms, or any person with a solid background in graphics and numerical techniques. | ||
| 650 | 0 |
_aMathematics. _911584 |
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| 650 | 0 |
_aImage processing _xDigital techniques. _94145 |
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| 650 | 0 |
_aComputer vision. _983587 |
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| 650 | 1 | 4 |
_aMathematics. _911584 |
| 650 | 2 | 4 |
_aComputer Imaging, Vision, Pattern Recognition and Graphics. _931569 |
| 700 | 1 |
_aBouville, Christian. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983589 |
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| 700 | 1 |
_aSantos, Luís Paulo. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983590 |
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| 700 | 1 |
_aBouatouch, Kadi. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _983592 |
|
| 710 | 2 |
_aSpringerLink (Online service) _983593 |
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| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031795664 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031795688 |
| 830 | 0 |
_aSynthesis Lectures on Computer Graphics and Animation, _x1933-9003 _983594 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-79567-1 |
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| 942 | _cEBK | ||
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