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Real-time people tracking for mobile robots using thermal vision
University of T ubingen. (Department of Computer Science)
Örebro University, Department of Technology. (Learning Systems Lab)
University of Lincoln. (Department of Computing and Informatics)
2006 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 54, no 9, p. 729-739Article in journal (Refereed) Published
Abstract [en]

This paper presents a vision-based approach for tracking people on a mobile robot using thermal images. The approach combines a particle filter with two alternative measurement models that are suitable for real-time tracking. With this approach a person can be detected independently from current light conditions and in situations where no skin colour is visible. In addition, the paper presents a comprehensive, quantitative evaluation of the different methods on a mobile robot in an office environment, for both single and multiple persons. The results show that the measurement model that was learned from local greyscale features could improve on the performance of the elliptic contour model, and that both models could be combined to further improve performance with minimal extra computational cost.

Place, publisher, year, edition, pages
2006. Vol. 54, no 9, p. 729-739
Keywords [en]
unified tracking, people detection, autonomous robots, quantitative performance evaluation, adaptive boosting
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3442DOI: 10.1016/j.robot.2006.04.013OAI: oai:DiVA.org:oru-3442DiVA, id: diva2:137739
Note
Selected papers from the 2nd European Conference on Mobile Robots (ECMR ’05)Available from: 2007-07-19 Created: 2007-07-19 Last updated: 2018-01-13Bibliographically approved

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Cielniak, Grzegorz

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