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Memorias de investigación
Ponencias en congresos:
Robust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles
Año:2014
Áreas de investigación
  • Percepción visual,
  • Robots aéreos,
  • Robots autónomos,
  • Robots de inspección,
  • Percepción,
  • Inspección visual,
  • Visión en tiempo-real
Datos
Descripción
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.
Internacional
Si
Nombre congreso
IEEE International Conference on Robotics and Automation (ICRA)
Tipo de participación
960
Lugar del congreso
HONG KONG
Revisores
Si
ISBN o ISSN
978-1-4799-3685-4
DOI
10.1109/ICRA.2014.6907659
Fecha inicio congreso
31/05/2014
Fecha fin congreso
07/06/2014
Desde la página
5441
Hasta la página
5446
Título de las actas
Robust real-time vision-based aircraft tracking from Unmanned Aerial Vehicles
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Changhong Fu (UPM)
  • Autor: Adrián Carrió Fernández (UPM)
  • Autor: Miguel Ángel Olivares Mendez (UPM)
  • Autor: Ramon Suarez Fernandez (Universidad Politecnica de Madrid)
  • Autor: Pascual Campoy Cervera (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
  • Departamento: Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial
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