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Supervised and Unsupervised Linear Learning Techniques for Visual Place Recognition in Changing Environments
Örebro University, School of Science and Technology, Örebro University, Sweden. (Centre for Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0003-3788-499X
Queensland University of Technology, Brisbane, Australia. (Australian Centre for Robotics Vision)
2016 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 32, no 3, 600-613 p.Article in journal (Refereed) Published
Abstract [en]

This paper investigates the application of linear learning techniques to the place recognition problem. We present two learning methods, a supervised change prediction technique based on linear regression and an unsupervised change removal technique based on principal component analysis, and investigate how the performance of each is affected by the choice of training data. We show that the change prediction technique presented here succeeds only if it is provided with appropriate and adequate training data, which can be challenging for a mobile robotic system operating in an uncontrolled environment. In contrast, change removal can improve place recognition performance even when trained with as few as 100 samples. This paper shows that change removal can be combined with a number of different image descriptors and can improve performance across a range of different appearance conditions.

Place, publisher, year, edition, pages
IEEE , 2016. Vol. 32, no 3, 600-613 p.
Keyword [en]
Changing environments, learning about change, linear regression, principal component analysis (PCA), visual place recognition.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-50431DOI: 10.1109/TRO.2016.2545711ISI: 000378528900009Scopus ID: 2-s2.0-84968764258OAI: oai:DiVA.org:oru-50431DiVA: diva2:931021
Note

Funding Agencies:

Australian Research Council FT140101229

Microsoft Research Faculty Fellowship

Available from: 2016-05-26 Created: 2016-05-26 Last updated: 2016-07-28Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
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