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

Blanco Adán, Carlos Roberto del and Mohedano del Pozo, Raúl and García Santos, Narciso and Salgado Álvarez de Sotomayor, Luis and Jaureguizar Núñez, Fernando (2008). Color-based 3D particle filtering for robust tracking in heterogeneous environments. In: "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. https://doi.org/10.1109/ICDSC.2008.4635690.

Description

Title: Color-based 3D particle filtering for robust tracking in heterogeneous environments
Author/s:
  • Blanco Adán, Carlos Roberto del
  • Mohedano del Pozo, Raúl
  • García Santos, Narciso
  • Salgado Álvarez de Sotomayor, Luis
  • Jaureguizar Núñez, Fernando
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
Event Dates: 07/09/2008-11/09/2008
Event Location: San Francisco, Estados Unidos
Title of Book: Proceedings of 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008
Date: 2008
ISBN: 978-1-4244-2664-5
Subjects:
Freetext Keywords: Multi-camera, Particle Filter, 3D Tracking, Color Descriptor, Visual Surveillance
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (672kB) | Preview

Abstract

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.

More information

Item ID: 3799
DC Identifier: http://oa.upm.es/3799/
OAI Identifier: oai:oa.upm.es:3799
DOI: 10.1109/ICDSC.2008.4635690
Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04635690
Deposited by: Memoria Investigacion
Deposited on: 30 Jul 2010 08:32
Last Modified: 20 Apr 2016 13:16
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM