License: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported license (CC BY-NC-ND 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.VLUDS.2010.20
URN: urn:nbn:de:0030-drops-30934
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2011/3093/
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Denker, Klaus ; Umlauf, Georg

Survey on Benchmarks for a GPU Based Multi Camera Stereo Matching Algorithm

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Abstract

Stereo matching algorithms and multi camera reconstruction algorithms are usually compared using benchmarks. These benchmarks compare the quality of the resulting depth map or reconstructed surface mesh. We describe the differences between several known stereo and multi-view stereo benchmarks and their various datasets. Also the modifications that are necessary to use our own GPU based multi camera stereo matching algorithm with the data from these benchmarks are discussed.

BibTeX - Entry

@InProceedings{denker_et_al:OASIcs:2011:3093,
  author =	{Klaus Denker and Georg Umlauf},
  title =	{{Survey on Benchmarks for a GPU Based Multi Camera Stereo Matching Algorithm}},
  booktitle =	{Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop)},
  pages =	{20--26},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-29-3},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{19},
  editor =	{Ariane Middel and Inga Scheler and Hans Hagen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2011/3093},
  URN =		{urn:nbn:de:0030-drops-30934},
  doi =		{10.4230/OASIcs.VLUDS.2010.20},
  annote =	{Keywords: Stereo matching, Multi camera, GPU}
}

Keywords: Stereo matching, Multi camera, GPU
Collection: Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop)
Issue Date: 2011
Date of publication: 13.04.2011

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