Vehicle detection and tracking using homography-based plane rectification and particle filtering

Arróspide Laborda, Jon; Salgado Álvarez de Sotomayor, Luis y Nieto Doncel, Marcos (2010). Vehicle detection and tracking using homography-based plane rectification and particle filtering. En: "IEEE Intelligent Vehicles Symposium, IV 2010", 21/06/2010 - 24/06/2010, San Diego, California, EEUU. ISBN 978-1-4244-7866-8.

Descripción

Título: Vehicle detection and tracking using homography-based plane rectification and particle filtering
Autor/es:
  • Arróspide Laborda, Jon
  • Salgado Álvarez de Sotomayor, Luis
  • Nieto Doncel, Marcos
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: IEEE Intelligent Vehicles Symposium, IV 2010
Fechas del Evento: 21/06/2010 - 24/06/2010
Lugar del Evento: San Diego, California, EEUU
Título del Libro: Proceedings of the IEEE Intelligent Vehicles Symposium, IV 2010
Fecha: Agosto 2010
ISBN: 978-1-4244-7866-8
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 9222
Identificador DC: http://oa.upm.es/9222/
Identificador OAI: oai:oa.upm.es:9222
URL Oficial: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5547980&tag=1
Depositado por: Memoria Investigacion
Depositado el: 18 Oct 2011 07:52
Ultima Modificación: 20 Abr 2016 17:43
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