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Lightweight, Viewpoint-Invariant Visual Place Recognition in Changing Environments
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-3788-499X
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-2953-1564
2018 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 3, no 2, p. 957-964Article in journal (Refereed) Published
Abstract [en]

This paper presents a viewpoint-invariant place recognition algorithm which is robust to changing environments while requiring only a small memory footprint. It demonstrates that condition-invariant local features can be combined with Vectors of Locally Aggregated Descriptors (VLAD) to reduce high-dimensional representations of images to compact binary signatures while retaining place matching capability across visually dissimilar conditions. This system provides a speed-up of two orders of magnitude over direct feature matching, and outperforms a bag-of-visual-words approach with near-identical computation speed and memory footprint. The experimental results show that single-image place matching from non-aligned images can be achieved in visually changing environments with as few as 256 bits (32 bytes) per image.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 3, no 2, p. 957-964
Keywords [en]
Visual-based navigation, recognition, localization
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-64652DOI: 10.1109/LRA.2018.2793308ISI: 000424646100015OAI: oai:DiVA.org:oru-64652DiVA, id: diva2:1178647
Note

Funding Agency:

Semantic Robots Research Profile - Swedish Knowledge Foundation

Available from: 2018-01-30 Created: 2018-01-30 Last updated: 2018-02-28Bibliographically approved

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Lowry, StephanieAndreasson, Henrik

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CiteExportLink to record
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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
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