Color-based 3D particle filtering for robust tracking in heterogeneous environments

Blanco Adán, Carlos Roberto del; Mohedano del Pozo, Raúl; García Santos, Narciso; Salgado Álvarez de Sotomayor, Luis y Jaureguizar Núñez, Fernando (2008). Color-based 3D particle filtering for robust tracking in heterogeneous environments. En: "2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008", 07/09/2008-11/09/2008, San Francisco, Estados Unidos. ISBN 978-1-4244-2664-5.

Descripción

Título: Color-based 3D particle filtering for robust tracking in heterogeneous environments
Autor/es:
  • Blanco Adán, Carlos Roberto del
  • Mohedano del Pozo, Raúl
  • García Santos, Narciso
  • Salgado Álvarez de Sotomayor, Luis
  • Jaureguizar Núñez, Fernando
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
Fechas del Evento: 07/09/2008-11/09/2008
Lugar del Evento: San Francisco, Estados Unidos
Título del Libro: Proceedings of 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
Fecha: 2008
ISBN: 978-1-4244-2664-5
Materias:
Palabras Clave Informales: Multi-camera, Particle Filter, 3D Tracking, Color Descriptor, Visual Surveillance
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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URL Oficial: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04635690

Resumen

Most multi-camera 3D tracking and positioning systems rely on several independent 2D tracking modules applied over individual camera streams, fused using both geometrical relationships across cameras and/or observed appearance of objects. However, 2D tracking systems suffer inherent difficulties due to point of view limitations (perceptually similar foreground and background regions causing fragmentation of moving objects, occlusions, etc.) and, therefore, 3D tracking based on partially erroneous 2D tracks are likely to fail when handling multiple-people interaction. In this paper, we propose a Bayesian framework for combining 2D low-level cues from multiple cameras directly into the 3D world through 3D Particle Filters. This novel method (direct 3D operation) allows the estimation of the probability of a certain volume being occupied by a moving object, using 2D motion detection and color features as state observations of the Particle Filter framework. For this purpose, an efficient color descriptor has been implemented, which automatically adapts itself to image noise, proving able to deal with changes in illumination and shape variations. The ability of the proposed framework to correctly track multiple 3D objects over time is tested on a real indoor scenario, showing satisfactory results.

Más información

ID de Registro: 3799
Identificador DC: http://oa.upm.es/3799/
Identificador OAI: oai:oa.upm.es:3799
Depositado por: Memoria Investigacion
Depositado el: 30 Jul 2010 08:32
Ultima Modificación: 20 Abr 2016 13:16
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