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When patches match - a statistical view on matching under illumination variation
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University of Frankfurt, Germany.
Goethe University of Frankfurt, Germany.
2014 (English)In: 2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), IEEE COMPUTER SOC , 2014, 4364-4369 p.Conference paper, Published paper (Refereed)
Abstract [en]

We discuss matching measures (scores and residuals) for comparing image patches under unknown affine photometric (=intensity) transformations. In contrast to existing methods, we derive a fully symmetric matching measure which reflects the fact that both copies of the signal are affected by measurement errors (noise), not only one. As it turns out, this evolves into an eigensystem problem; however a simple direct solution for all entities of interest can be given. We strongly advocate for constraining the estimated gain ratio and the estimated mean value offset to realistic ranges, thus preventing the matching scheme from locking into unrealistic correspondences.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC , 2014. 4364-4369 p.
Series
International Conference on Pattern Recognition, ISSN 1051-4651
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-121335DOI: 10.1109/ICPR.2014.747ISI: 000359818004084ISBN: 978-1-4799-5208-3 (print)OAI: oai:DiVA.org:liu-121335DiVA: diva2:853439
Conference
22nd International Conference on Pattern Recognition (ICPR)
Available from: 2015-09-14 Created: 2015-09-14 Last updated: 2015-09-14

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