A Low-Level Active Vision Framework for Collaborative Unmanned Aircraft Systems
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 (Refereed)
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.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8925
Visual tracking; Visual surveillance; Micro UAV; Active vision
Computer Vision and Robotics (Autonomous Systems) Computer Science
IdentifiersURN: 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 (online)OAI: oai:DiVA.org:liu-115847DiVA: diva2:796839
13th European Conference on Computer Vision (ECCV) Switzerland, September 6-7 and 12