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Improved data association and occlusion handling for vision-based people tracking by mobile robots
Örebro University, Department of Technology. (Learning Systems Lab)
Örebro University, Department of Technology. Department of Computing and Informatics, University of Lincoln.
Örebro University, Department of Technology. (Learning Systems Lab)ORCID iD: 0000-0003-0217-9326
2007 (English)In: IEEE/RSJ international conference on intelligent robots and systems, 2007. IROS 2007, 2007, 3436-3441 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an approach for tracking multiple persons using a combination of colour and thermal vision sensors on a mobile robot. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is then incorporated into the tracker.

Place, publisher, year, edition, pages
2007. 3436-3441 p.
Keyword [en]
person tracking, robot vision, occlusion handling
National Category
Engineering and Technology Computer and Information Science
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3271DOI: 10.1109/IROS.2007.4399507ISBN: 978-1-4244-0912-9 (print)OAI: oai:DiVA.org:oru-3271DiVA: diva2:137568
Conference
IEEE/RSJ international conference on intelligent robots and systems, 2007. IROS 2007
Available from: 2008-11-28 Created: 2008-11-28 Last updated: 2017-10-18Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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