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Obtaining reliable depth maps for robotic applications from a quad-camera system
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
Production and Management Engineering Dept., Democritus University of Thrace, Greece.
2009 (English)In: INTELLIGENT ROBOTICS AND APPLICATIONS, PROCEEDINGS, Berlin: Springer Berlin/Heidelberg, 2009, Vol. 5928 LNAI, 906-916 p.Conference paper, Published paper (Other academic)
Abstract [en]

Autonomous navigation behaviors in robotics often require reliable depth maps. The use of vision sensors is the most popular choice in such tasks. On the other hand, accurate vision-based depth computing methods suffer from long execution times. This paper proposes a novel quad-camera based system able to calculate fast and accurately a single depth map of a scenery. The four cameras are placed on the corners of a square. Thus, three, differently oriented, stereo pairs result when considering a single reference image (namely an horizontal, a vertical and a diagonal pair). The proposed system utilizes a custom tailored, simple, rapidly executed stereo correspondence algorithm applied to each stereo pair. This way, the computational load is kept within reasonable limits. A reliability measure is used in order to validate each point of the resulting disparity maps. Finally, the three disparity maps are fused together according to their reliabilities. The maximum reliability is chosen for every pixel. The final output of the proposed system is a highly reliable depth map which can be used for higher level robotic behaviors.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2009. Vol. 5928 LNAI, 906-916 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743
Keyword [en]
Disparity maps fusion, Quad-camera system, Stereo vision, Autonomous navigation, Camera systems, Computational loads, Computing methods, Depth Map, Disparity map, Execution time, Maximum reliability, Reference image, Reliability measure, Robotic applications, Robotic behavior, Stereo correspondences, Stereo pair, Vision based, Vision sensors, Cameras, Neurosurgery, Reliability, Robotics, Robots
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:kth:diva-50995DOI: 10.1007/978-3-642-10817-4_89ISI: 000279602600089ISBN: 978-3-642-10816-7 (print)OAI: oai:DiVA.org:kth-50995DiVA: diva2:463166
Conference
2nd International Conference Intelligent Robotics and Applications. Singapore, SINGAPORE. DEC 16-18, 2009
Note
QC 20111212Available from: 2011-12-08 Created: 2011-12-08 Last updated: 2011-12-12Bibliographically approved

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Nalpantidis, Lazaros
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Total: 15 hits
CiteExportLink to record
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Cite
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