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A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-6096-3648
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-3450-988X
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2015 (English)In: COMPUTER VISION - ECCV 2014 WORKSHOPS, PT I / [ed] Lourdes Agapito, Michael M. Bronstein and Carsten Rother, Springer Publishing Company, 2015, Vol. 8925, 223-237 p.Conference paper, Published paper (Refereed)
Abstract [en]

Micro unmanned aerial vehicles are becoming increasingly interesting for aiding and collaborating with human agents in myriads of applications, but in particular they are useful for monitoring inaccessible or dangerous areas. In order to interact with and monitor humans, these systems need robust and real-time computer vision subsystems that allow to detect and follow persons.

In this work, we propose a low-level active vision framework to accomplish these challenging tasks. Based on the LinkQuad platform, we present a system study that implements the detection and tracking of people under fully autonomous flight conditions, keeping the vehicle within a certain distance of a person. The framework integrates state-of-the-art methods from visual detection and tracking, Bayesian filtering, and AI-based control. The results from our experiments clearly suggest that the proposed framework performs real-time detection and tracking of persons in complex scenarios

Place, publisher, year, edition, pages
Springer Publishing Company, 2015. Vol. 8925, 223-237 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8925
Keyword [en]
Visual tracking; Visual surveillance; Micro UAV; Active vision
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-115847DOI: 10.1007/978-3-319-16178-5_15ISI: 000362493800015ISBN: 978-3-319-16177-8 (print)ISBN: 978-3-319-16178-5 (print)OAI: oai:DiVA.org:liu-115847DiVA: diva2:796839
Conference
13th European Conference on Computer Vision (ECCV) Switzerland, September 6-7 and 12
Available from: 2015-03-20 Created: 2015-03-20 Last updated: 2016-05-04Bibliographically approved

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Danelljan, MartinKhan, Fahad ShahbazFelsberg, MichaelGranström, KarlHeintz, FredrikRudol, PiotrWzorek, MariuszKvarnström, JonasDoherty, Patrick

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Danelljan, MartinKhan, Fahad ShahbazFelsberg, MichaelGranström, KarlHeintz, FredrikRudol, PiotrWzorek, MariuszKvarnström, JonasDoherty, Patrick
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Computer VisionThe Institute of TechnologyFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)Automatic ControlArtificial Intelligence and Intergrated Computer systems
Computer Vision and Robotics (Autonomous Systems)Computer Science

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