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

Blanco Adán, Carlos Roberto del; Jaureguizar Núñez, Fernando; Salgado Álvarez de Sotomayor, Luis y García Santos, Narciso (2009). Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion. En: "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.

Descripción

Título: Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion
Autor/es:
  • Blanco Adán, Carlos Roberto del
  • Jaureguizar Núñez, Fernando
  • Salgado Álvarez de Sotomayor, Luis
  • García Santos, Narciso
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Fechas del Evento: 2-4 de Septiembre del 2009
Lugar del Evento: Génova, Italia
Título del Libro: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Fecha: 2009
ISBN: 978-0-7695-3718-4
Materias:
Palabras Clave Informales: Tracking, ego-motion, moving camera, Particle Filter, spatiogram, affine transformation, independent moving objects
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (444kB) | Vista Previa

Resumen

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.

Más información

ID de Registro: 7267
Identificador DC: http://oa.upm.es/7267/
Identificador OAI: oai:oa.upm.es:7267
URL Oficial: http://www.computer.org/portal/web/csdl/proceedings/a#5
Depositado por: Doctor Carlos Roberto del Blanco Adán
Depositado el: 27 May 2011 11:55
Ultima Modificación: 20 Abr 2016 16:27
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM