Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.

Fu, Changhong and Carrio Fernández, Adrián and Olivares Méndez, Miguel Ángel and Suárez Fernández, Ramón and Campoy Cervera, Pascual (2014). Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.. In: "2014 IEEE International Conference on Robotics & Automation (ICRA)", May 31 - June 7, 2014, Hong Kong, China. ISBN 978-1-4799-3685-4. pp. 5441-5446.

Description

Title: Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.
Author/s:
  • Fu, Changhong
  • Carrio Fernández, Adrián
  • Olivares Méndez, Miguel Ángel
  • Suárez Fernández, Ramón
  • Campoy Cervera, Pascual
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2014 IEEE International Conference on Robotics & Automation (ICRA)
Event Dates: May 31 - June 7, 2014
Event Location: Hong Kong, China
Title of Book: 2014 IEEE International Conference on Robotics & Automation (ICRA)
Date: 2014
ISBN: 978-1-4799-3685-4
Subjects:
Faculty: E.T.S.I. Industriales (UPM)
Department: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
UPM's Research Group: Computer Vision CVG
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainDPI2010-20751-C02-01CICYTUnspecifiedUnspecified
Government of SpainTSI-020100-2011-363UnspecifiedUnspecifiedE-Vision Project
FP7FP7-ICT-231143UnspecifiedUnspecifiedOMNIWORKS project (an experiment funded in the context of the ECHORD project)

More information

Item ID: 37645
DC Identifier: http://oa.upm.es/37645/
OAI Identifier: oai:oa.upm.es:37645
Official URL: http://www.icra2014.com/
Deposited by: Memoria Investigacion
Deposited on: 17 Sep 2015 15:20
Last Modified: 21 Sep 2015 15:17
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