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

Fu, Changhong; Carrio Fernández, Adrián; Olivares Méndez, Miguel Ángel; Suárez Fernández, Ramón y Campoy Cervera, Pascual (2014). Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.. En: "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.

Descripción

Título: Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.
Autor/es:
  • Fu, Changhong
  • Carrio Fernández, Adrián
  • Olivares Méndez, Miguel Ángel
  • Suárez Fernández, Ramón
  • Campoy Cervera, Pascual
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2014 IEEE International Conference on Robotics & Automation (ICRA)
Fechas del Evento: May 31 - June 7, 2014
Lugar del Evento: Hong Kong, China
Título del Libro: 2014 IEEE International Conference on Robotics & Automation (ICRA)
Fecha: 2014
ISBN: 978-1-4799-3685-4
Materias:
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
Grupo Investigación UPM: Computer Vision CVG
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
Gobierno de EspañaDPI2010-20751-C02-01CICYTSin especificarSin especificar
Gobierno de EspañaTSI-020100-2011-363Sin especificarSin especificarE-Vision Project
FP7FP7-ICT-231143Sin especificarSin especificarOMNIWORKS project (an experiment funded in the context of the ECHORD project)

Más información

ID de Registro: 37645
Identificador DC: http://oa.upm.es/37645/
Identificador OAI: oai:oa.upm.es:37645
URL Oficial: http://www.icra2014.com/
Depositado por: Memoria Investigacion
Depositado el: 17 Sep 2015 15:20
Ultima Modificación: 21 Sep 2015 15:17
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