Peter WonkaORCID iD, Michael WimmerORCID iD, Kaichi Zhou, Stefan Maierhofer, Gerd Hesina, Alexander Reshetov
Guided Visibility Sampling
ACM Transactions on Graphics, 25(3):494-502, July 2006. [Preprint]

Information

  • Publication Type: Journal Paper with Conference Talk
  • Workgroup(s)/Project(s):
  • Date: July 2006
  • Journal: ACM Transactions on Graphics
  • Volume: 25
  • Number: 3
  • Note: Proceedings ACM SIGGRAPH 2006
  • Location: Boston, USA
  • Lecturer:
  • ISSN: 0730-0301
  • Event: ACM SIGGRAPH 2006
  • DOI: 10.1145/1141911.1141914
  • Conference date: 30. July 2006 – 4. August 2006
  • Pages: 494 – 502
  • Keywords: visibility, visibility sampling, occlusion culling, PVS

Abstract

This paper addresses the problem of computing the triangles visible from a region in space. The proposed aggressive visibility solution is based on stochastic ray shooting and can take any triangular model as input. We do not rely on connectivity information, volumetric occluders, or the availability of large occluders, and can therefore process any given input scene. The proposed algorithm is practically memoryless, thereby alleviating the large memory consumption problems prevalent in several previous algorithms. The strategy of our algorithm is to use ray mutations in ray space to cast rays that are likely to sample new triangles. Our algorithm improves the sampling efficiency of previous work by over two orders of magnitude.

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BibTeX

@article{WONKA-2006-GVS,
  title =      "Guided Visibility Sampling",
  author =     "Peter Wonka and Michael Wimmer and Kaichi Zhou and Stefan
               Maierhofer and Gerd Hesina and Alexander Reshetov",
  year =       "2006",
  abstract =   "This paper addresses the problem of computing the triangles
               visible from a region in space. The proposed aggressive
               visibility solution is based on stochastic ray shooting and
               can take any triangular model as input. We do not rely on
               connectivity information, volumetric occluders, or the
               availability of large occluders, and can therefore process
               any given input scene. The proposed algorithm is practically
               memoryless, thereby alleviating the large memory consumption
               problems prevalent in several previous algorithms. The
               strategy of our algorithm is to use ray mutations in ray
               space to cast rays that are likely to sample new triangles.
               Our algorithm improves the sampling efficiency of previous
               work by over two orders of magnitude.",
  month =      jul,
  journal =    "ACM Transactions on Graphics",
  volume =     "25",
  number =     "3",
  note =       "Proceedings ACM SIGGRAPH 2006",
  issn =       "0730-0301",
  doi =        "10.1145/1141911.1141914",
  pages =      "494--502",
  keywords =   "visibility, visibility sampling, occlusion culling, PVS",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2006/WONKA-2006-GVS/",
}