oru.sePublications
Change search
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
SIFT, SURF and seasons: long-term outdoor localization using local features
Örebro University, Örebro, Sweden. (AASS)
Örebro University, Department of Technology. (AASS)ORCID iD: 0000-0003-0217-9326
2007 (English)In: ECMR 2007: Proceedings of the European Conference on Mobile Robots, 2007, p. 253-258Conference paper, Published paper (Refereed)
Abstract [en]

Local feature matching has become a commonly used method to compare images. For mobile robots, a reliable method for comparing images can constitute a key component for localization and loop closing tasks. In this paper, we address the issues of outdoor appearance-based topological localization for a mobile robot over time. Our data sets, each consisting of a large number of panoramic images, have been acquired over a period of nine months with large seasonal changes (snowcovered ground, bare trees, autumn leaves, dense foliage, etc.). Two different types of image feature algorithms, SIFT and the more recent SURF, have been used to compare the images. We show that two variants of SURF, called U-SURF and SURF-128, outperform the other algorithms in terms of accuracy and speed.

Place, publisher, year, edition, pages
2007. p. 253-258
National Category
Engineering and Technology Computer and Information Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-4263OAI: oai:DiVA.org:oru-4263DiVA, id: diva2:138562
Conference
3rd European conference on mobile robots, ECMR '07, Freiburg, Germany, September 19-21, 2007
Available from: 2007-12-13 Created: 2007-12-13 Last updated: 2018-06-12Bibliographically approved

Open Access in DiVA

SIFT, SURF and Seasons: Long-term Outdoor Localization Using Local Features(1929 kB)44 downloads
File information
File name FULLTEXT01.pdfFile size 1929 kBChecksum SHA-512
6c1b61919dfd3551ca782ec1a0995ffbb03540ec9481646468478f70fa063e368cda63493066d4546f722ddcd9b69c5a03dbd6e83b1489c3a05bafc9726bcf6a
Type fulltextMimetype application/pdf

Other links

fulltext

Authority records BETA

Lilienthal, Achim J.

Search in DiVA

By author/editor
Lilienthal, Achim J.
By organisation
Department of Technology
Engineering and TechnologyComputer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 44 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 621 hits
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