Memorias de investigación
Communications at congresses:
Real-time Adaptive Multi-Classifer Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles
Year:2013

Research Areas
  • Automatic

Information
Abstract
This paper presents a novel robust visual tracking framework, based on discrim- inative methods, for Unmanned Aerial Vehicle (UAV) to track an arbitrary 2D/3D target with no prior knowledge at real-time frame rates, that is called the Adaptive Multi-Classi?er Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifers (MC) are applied to classify the compressed positive and negative samples in downsampling-based Multiple Resolutions (MR) structure in order to update and detect the current target. And the sample importance has been integrated into this framework to improve the tracking stablity and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in di erent type of public image databases and real ight-based aerial image datasets ?rstly, then the framework has been applied in the O shore Floating Platform (OFP) Inspection task. The evaluation and application results show that this framework is more robust, e?cient and accurated against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the ?rst work to present this framework for solving the online learning and tracking freewill 2D/3D targets problems in the UAV.
International
Si
Congress
2nd IFAC Workshop on Research, Education and Development of Unmanned Aerial Systems (2013)
960
Place
University of Technology of Compiegne, Compiegne, France
Reviewers
Si
ISBN/ISSN
1474-6670
Start Date
20/11/2013
End Date
22/11/2013
From page
99
To page
106
Research, Education and Development of Unmanned Aerial Systems
Participants

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Computer Vision
  • Departamento: Automática, Ingeniería Electrónica e Informática Industrial
  • Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC