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Active people recognition using thermal and grey images on a mobile security robot
University of Tubingen.
Örebro University, Department of Technology. AASS. (Learning Systems Lab)
Örebro University, Department of Technology. (Learning Systems Lab)
2005 (English)In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005): IROS 2005 IEEE/RSJ -, 2005, p. 2103-2108Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a vision-based approach to detect, track and identify people on a mobile robot in real time. While most vision systems for tracking people on mobile robots use skin color information, we present an approach using thermal images and a fast contour model together with a Particle Filter. With this method a person can be detected independently from current light conditions and in situations were no skin color is visible (the person is not close or does not face the robot). Tracking in thermal images is used as an attention system to get an estimate of the position of a person. Based on this estimate we use a pan-tilt camera to zoom to the expected face region and apply a fast face tracker in combination with face recognition to identify the person.

Place, publisher, year, edition, pages
2005. p. 2103-2108
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3962DOI: 10.1109/IROS.2005.1545530OAI: oai:DiVA.org:oru-3962DiVA, id: diva2:138261
Conference
2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005, (IROS 2005), Edmonton, Alberta, Canada, 2-6 Aug. 2005
Available from: 2007-08-27 Created: 2007-08-27 Last updated: 2018-01-13Bibliographically approved

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Cielniak, GrzegorzDuckett, Tom

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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
  • rtf