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Obstacle detection for thin horizontal structures
University of Skövde, School of Technology and Society.
Halmstad University.
2008 (English)In: World Congress on Engineering and Computer Science 2008, IAENG , 2008, p. 689-693Conference paper, Published paper (Refereed)
Abstract [en]

 Abstract— Many vision-based approaches for obstacle detection often state that vertical thin structure is of importance, e.g. poles and trees. However, there are also problem in detecting thin horizontal structures. In an industrial case there are horizontal objects, e.g. cables and fork lifts, and slanting objects, e.g. ladders, that also has to be detected. This paper focuses on the problem to detect thin horizontal structures. The system uses three cameras, situated as a horizontal pair and a vertical pair, which makes it possible to also detect thin horizontal structures. A comparison between a sparse disparity map based on edges and a dense disparity map with a column and row filter is made. Both methods use the Sum of Absolute Difference to compute the disparity maps. Special interest has been in scenes with thin horizontal objects. Tests show that a trinocular system with the sparse dense method based on the Canny detector works better for the environments we have tested.

 

Place, publisher, year, edition, pages
IAENG , 2008. p. 689-693
Keyword [en]
Computer vision, Obstacle detection, Stereo vision, Thin structures
Identifiers
URN: urn:nbn:se:his:diva-2409ISBN: 978-988-98671-0-2 OAI: oai:DiVA.org:his-2409DiVA, id: diva2:127163
Available from: 2008-12-05 Created: 2008-12-01 Last updated: 2017-11-27

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Hedenberg, Klas

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf