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  • Research Article
  • Open Access

Robust Tracking in Aerial Imagery Based on an Ego-Motion Bayesian Model

  • 1Email author,
  • 1 and
  • 1
EURASIP Journal on Advances in Signal Processing20102010:837405

  • Received: 23 November 2009
  • Accepted: 17 June 2010
  • Published:


A novel strategy for object tracking in aerial imagery is presented, which is able to deal with complex situations where the camera ego-motion cannot be reliably estimated due to the aperture problem (related to low structured scenes), the strong ego-motion, and/or the presence of independent moving objects. The proposed algorithm is based on a complex modeling of the dynamic information, which simulates both the object and the camera dynamics to predict the putative object locations. In this model, the camera dynamics is probabilistically formulated as a weighted set of affine transformations that represent possible camera ego-motions. This dynamic model is used in a Particle Filter framework to distinguish the actual object location among the multiple candidates, that result from complex cluttered backgrounds, and the presence of several moving objects. The proposed strategy has been tested with the aerial FLIR AMCOM dataset, and its performance has been also compared with other tracking techniques to demonstrate its efficiency.


  • Particle Filter
  • Bayesian Model
  • Object Tracking
  • Object Location
  • Affine Transformation

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Authors’ Affiliations

Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid, 28040, Madrid, Spain


© Carlos R. del Blanco et al. 2010

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.