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Visual Place Recognition: A Survey
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS MRO Lab)
The Australian Centre for Robotic Vision, School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, Australia.
The Mobile Robotics Group, Department of Engineering Science, University of Oxford, Oxford, U.K..
The Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, USA.
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2016 (English)In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 32, no 1, 1-19 p.Article in journal (Refereed) Published
Abstract [en]

Visual place recognition is a challenging problem due to the vast range of ways in which the appearance of real-world places can vary. In recent years, improvements in visual sensing capabilities, an ever-increasing focus on long-term mobile robot autonomy, and the ability to draw on state-of-the-art research in other disciplines - particularly recognition in computer vision and animal navigation in neuroscience - have all contributed to significant advances in visual place recognition systems. This paper presents a survey of the visual place recognition research landscape. We start by introducing the concepts behind place recognition - the role of place recognition in the animal kingdom, how a "place" is defined in a robotics context, and the major components of a place recognition system. Long-term robot operations have revealed that changing appearance can be a significant factor in visual place recognition failure; therefore, we discuss how place recognition solutions can implicitly or explicitly account for appearance change within the environment. Finally, we close with a discussion on the future of visual place recognition, in particular with respect to the rapid advances being made in the related fields of deep learning, semantic scene understanding, and video description.

Place, publisher, year, edition, pages
IEEE Robotics and Automation Society, 2016. Vol. 32, no 1, 1-19 p.
Keyword [en]
Visual place recognition, place recognition
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-46997DOI: 10.1109/TRO.2015.2496823ISI: 000370764000001OAI: oai:DiVA.org:oru-46997DiVA: diva2:877953
Note

Funding Agencies:

ARC Future Fellowship FT140101229

Microsoft Research Faculty Fellowship

Australian Centre for Robotic Vision

Available from: 2015-12-08 Created: 2015-12-08 Last updated: 2016-03-22Bibliographically approved

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Lowry, Stephanie
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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