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Pose-Invariant 3D Object Recognition Using Linear Combination of 2D Views and Evolutionary Optimisation
University College London. (Computer Vision)
University College London. (Computer Vision)
2007 (English)In: Proceedings of the ICCTA'07, 2007, 645-649 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we present a method for model-based recognition of 3d objects from a small number of 2d intensity images taken from nearby, but otherwise arbitrary viewpoints. Our method works by linearly combining images from two (or more) viewpoints of a 3d object to synthesise novel views of the object. The object is recognised in a target image by matching to such a synthesised, novel view. All that is required is the recovery of the linear combination parameters, and since we are working directly with pixel intensities, we suggest searching the parameter space using an evolutionary optimisation algorithm in order to efficiently recover the optimal parameters and thus recognise the object in the scene.

Place, publisher, year, edition, pages
2007. 645-649 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-52177DOI: 10.1109/ICCTA.2007.105ISBN: 0-7695-2770-1 (print)OAI: oai:DiVA.org:liu-52177DiVA: diva2:280081
Conference
International Conference on Computing: Theory and Applications
Available from: 2010-09-29 Created: 2009-12-08 Last updated: 2010-09-29Bibliographically approved

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Zografos, Vasileios

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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