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Visual place recognition techniques for pose estimation in changing environments
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS MRO Lab)ORCID iD: 0000-0003-3788-499X
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS MRO Lab)ORCID iD: 0000-0002-2953-1564
2016 (English)In: Visual Place Recognition: What is it Good For? workshop, Robotics: Science and Systems (RSS) 2016, 2016Conference paper, Published paper (Other academic)
Abstract [en]

This paper investigates whether visual place recognition techniques can be used to provide pose estimation information for a visual SLAM system operating long-term in an environment where the appearance may change a great deal. It demonstrates that a combination of a conventional SURF feature detector and a condition-invariant feature descriptor such as HOG or conv3 can provide a method of determining the relative transformation between two images, even when there is both appearance change and rotation or viewpoint change.

Place, publisher, year, edition, pages
2016.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-56216OAI: oai:DiVA.org:oru-56216DiVA: diva2:1079851
Conference
Visual Place Recognition: What is it Good For? workshop, Robotics: Science and Systems (RSS) 2016, Ann Arbor, MI, USA, 19 June, 2016
Available from: 2017-03-09 Created: 2017-03-09 Last updated: 2017-03-09Bibliographically approved

Open Access in DiVA

Visual place recognition techniques for pose estimation in changing environments(861 kB)270 downloads
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File name FULLTEXT01.pdfFile size 861 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

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Lowry, StephanieHenrik, Andreasson
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School of Science and Technology, Örebro University, Sweden
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Total: 270 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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