Computer-generated imagery has become a central point in large and quickly growing areas such as computer animation, visual effects, architecture, high-quality visualization, and product design. A common requirement to all these areas is the efficient simulation of light transport from the light source to the sensor for image synthesis. This is a challenging task, as light can travel along all kinds of paths, and some paths are hard to find when computing the result numerically. The process of light propagation in a virtual scene is described by a path integral equation. This path integral is defined over the path space, the space of all possible light paths, on which photons travel from a light source to a virtual sensor. Monte Carlo approaches are employed for computing the path integral, where paths are stochastically generated (sampled). The integration, to compute an image of a virtual scene, in this space is challenging because of the mathematical properties of the integrand. In addition, the demand for both image quality and quantity requires shorter image rendering times, while imposing higher scene complexity at the same ti ... mehr

Zugehörige Institution(en) am KIT |
Institut für Visualisierung und Datenanalyse (IVD) |

Publikationstyp |
Hochschulschrift |

Jahr |
2017 |

Sprache |
Englisch |

Identifikator |
DOI(KIT): 10.5445/IR/1000068635 URN: urn:nbn:de:swb:90-686359 KITopen ID: 1000068635 |

Verlag |
Karlsruhe |

Umfang |
XXXV, 232 S. |

Abschlussart |
Dissertation |

Fakultät |
Fakultät für Informatik (INFORMATIK) |

Institut |
Institut für Visualisierung und Datenanalyse (IVD) |

Prüfungsdatum |
23.01.2017 |

Referent/Betreuer |
Prof. C. Dachsbacher |

Lizenz |
CC BY-SA 4.0: Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 4.0 International |

Schlagworte |
light transport, image synthesis, Markov chain Monte Carlo |

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