Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion

Blanco Adán, Carlos Roberto del and Jaureguizar Núñez, Fernando and Salgado Álvarez de Sotomayor, Luis and García Santos, Narciso (2009). Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion. In: "Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance", 2-4 de Septiembre del 2009, Génova, Italia. ISBN 978-0-7695-3718-4.

Description

Title: Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion
Author/s:
  • Blanco Adán, Carlos Roberto del
  • Jaureguizar Núñez, Fernando
  • Salgado Álvarez de Sotomayor, Luis
  • García Santos, Narciso
Item Type: Presentation at Congress or Conference (Article)
Event Title: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Event Dates: 2-4 de Septiembre del 2009
Event Location: Génova, Italia
Title of Book: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Date: 2009
ISBN: 978-0-7695-3718-4
Subjects:
Freetext Keywords: Tracking, ego-motion, moving camera, Particle Filter, spatiogram, affine transformation, independent moving objects
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to the object dynamics. The typical approach is to use a registration algorithm to compensate the camera motion. However, in situations involving several moving objects, and backgrounds highly affected by the aperture problem, image registration quality may be very low, decreasing dramatically the performance of the tracking. In this work, a novel approach is proposed to successfully tackle the tracking with moving cameras in complex situations, which involve several independent moving objects. The key idea is to compute several hypotheses for the camera motion, instead of estimating deterministically only one. These hypotheses are combined with the object dynamics in a Particle Filter framework to predict the most probable object locations. Then, each hypothetical object location is evaluated by the measurement model using a spatiogram, which is a region descriptor based on color and spatial distributions. Experimental results show that the proposed strategy allows to accurately track an object in complex situations affected by strong ego motion.

More information

Item ID: 7267
DC Identifier: http://oa.upm.es/7267/
OAI Identifier: oai:oa.upm.es:7267
Official URL: http://www.computer.org/portal/web/csdl/proceedings/a#5
Deposited by: Doctor Carlos Roberto del Blanco Adán
Deposited on: 27 May 2011 11:55
Last Modified: 20 Apr 2016 16:27
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