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Memorias de investigación
Communications at congresses:
Vehicle detection and tracking using homography-based plane rectification and particle filtering
Year:2010
Research Areas
  • Processing and signal analysis
Information
Abstract
This paper presents a full system for vehicle detection and tracking in non-stationary settings based on computer vision. The method proposed for vehicle detection exploits the geometrical relations between the elements in the scene so that moving objects (i.e., vehicles) can be detected by analyzing motion parallax. Namely, the homography of the road plane between successive images is computed. Most remarkably, a novel probabilistic framework based on Kalman filtering is presented for reliable and accurate homography estimation. The estimated homography is used for image alignment, which in turn allows to detect the moving vehicles in the image. Tracking of vehicles is performed on the basis of a multidimensional particle filter, which also manages the exit and entries of objects. The filter involves a mixture likelihood model that allows a better adaptation of the particles to the observed measurements. The system is specially designed for highway environments, where it has been proven to yield excellent results.
International
Si
Congress
IEEE Intelligent Vehicles Symposium, IV 2010
960
Place
San Diego (CA), USA
Reviewers
Si
ISBN/ISSN
978-1-4244-7866-8
10.1109/IVS.2010.5547980
Start Date
21/06/2010
End Date
24/06/2010
From page
150
To page
155
Proc. IEEE Intelligent Vehicles Symposium, IV 2010
Participants
  • Autor: Jon Arróspide Laborda (UPM)
  • Autor: Luis Salgado Alvarez de Sotomayor (UPM)
  • Autor: Marcos Nieto Doncel (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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