Robust Object Tracking in Infrared Video via Particle Filters

Autores
Comas, Edgardo Antonio; Stacul, Adrián; Delrieux, Claudio Augusto
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. A particle filter is initialized with these feature points, and the location of the object within the video frames is determined by the average value of the particles that have a greater similarity with the target. Our aim is to make possible unnupervised object tracking in unmanned night flights. Two different field tests were carried out to study the filter behaviour in comparison with previously used methods in the bibliography. The first one was tracking an unmanned aerial vehicle (UAV) in the open. The second one was to identify a heliport in a noisy infrared zenithal video take. In the first test, the UAV was followed by another positioning system simultaneously, thus allowing the comparison of both systems, and the evaluation in the improvement introduced by the particle algorithm.
Fil: Comas, Edgardo Antonio. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
Fil: Stacul, Adrián. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Ciencias de Las Imágenes; Argentina
Materia
IMAGE ANALYSIS
PATTERN RECOGNITION
TRACKING
PARTICLE FILTER
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/289483
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Robust Object Tracking in Infrared Video via Particle FiltersComas, Edgardo AntonioStacul, AdriánDelrieux, Claudio AugustoIMAGE ANALYSISPATTERN RECOGNITIONTRACKINGPARTICLE FILTERhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. A particle filter is initialized with these feature points, and the location of the object within the video frames is determined by the average value of the particles that have a greater similarity with the target. Our aim is to make possible unnupervised object tracking in unmanned night flights. Two different field tests were carried out to study the filter behaviour in comparison with previously used methods in the bibliography. The first one was tracking an unmanned aerial vehicle (UAV) in the open. The second one was to identify a heliport in a noisy infrared zenithal video take. In the first test, the UAV was followed by another positioning system simultaneously, thus allowing the comparison of both systems, and the evaluation in the improvement introduced by the particle algorithm.Fil: Comas, Edgardo Antonio. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; ArgentinaFil: Stacul, Adrián. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; ArgentinaFil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Ciencias de Las Imágenes; ArgentinaUniversitat Autònoma de Barcelona2020-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/289483Comas, Edgardo Antonio; Stacul, Adrián; Delrieux, Claudio Augusto; Robust Object Tracking in Infrared Video via Particle Filters; Universitat Autònoma de Barcelona; Electronic Letters on Computer Vision and Image Analysis; 19; 1; 7-2020; 1-141577-5097CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.5565/rev/elcvia.1185info:eu-repo/semantics/altIdentifier/url/https://elcvia.cvc.uab.cat/article/view/v19-n1-comasinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T14:34:58Zoai:ri.conicet.gov.ar:11336/289483instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 14:34:58.959CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Robust Object Tracking in Infrared Video via Particle Filters
title Robust Object Tracking in Infrared Video via Particle Filters
spellingShingle Robust Object Tracking in Infrared Video via Particle Filters
Comas, Edgardo Antonio
IMAGE ANALYSIS
PATTERN RECOGNITION
TRACKING
PARTICLE FILTER
title_short Robust Object Tracking in Infrared Video via Particle Filters
title_full Robust Object Tracking in Infrared Video via Particle Filters
title_fullStr Robust Object Tracking in Infrared Video via Particle Filters
title_full_unstemmed Robust Object Tracking in Infrared Video via Particle Filters
title_sort Robust Object Tracking in Infrared Video via Particle Filters
dc.creator.none.fl_str_mv Comas, Edgardo Antonio
Stacul, Adrián
Delrieux, Claudio Augusto
author Comas, Edgardo Antonio
author_facet Comas, Edgardo Antonio
Stacul, Adrián
Delrieux, Claudio Augusto
author_role author
author2 Stacul, Adrián
Delrieux, Claudio Augusto
author2_role author
author
dc.subject.none.fl_str_mv IMAGE ANALYSIS
PATTERN RECOGNITION
TRACKING
PARTICLE FILTER
topic IMAGE ANALYSIS
PATTERN RECOGNITION
TRACKING
PARTICLE FILTER
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. A particle filter is initialized with these feature points, and the location of the object within the video frames is determined by the average value of the particles that have a greater similarity with the target. Our aim is to make possible unnupervised object tracking in unmanned night flights. Two different field tests were carried out to study the filter behaviour in comparison with previously used methods in the bibliography. The first one was tracking an unmanned aerial vehicle (UAV) in the open. The second one was to identify a heliport in a noisy infrared zenithal video take. In the first test, the UAV was followed by another positioning system simultaneously, thus allowing the comparison of both systems, and the evaluation in the improvement introduced by the particle algorithm.
Fil: Comas, Edgardo Antonio. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
Fil: Stacul, Adrián. Ministerio de Defensa. Instituto de Investigaciones Científicas y Técnicas para la Defensa; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
Fil: Delrieux, Claudio Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Laboratorio de Ciencias de Las Imágenes; Argentina
description In this paper we investigate the effectiveness of particle filters for object tracking in infrared videos. Once the user identifies the target object to be followed in position and size, its most representative feature points are obtained by means of the SURF algorithm. A particle filter is initialized with these feature points, and the location of the object within the video frames is determined by the average value of the particles that have a greater similarity with the target. Our aim is to make possible unnupervised object tracking in unmanned night flights. Two different field tests were carried out to study the filter behaviour in comparison with previously used methods in the bibliography. The first one was tracking an unmanned aerial vehicle (UAV) in the open. The second one was to identify a heliport in a noisy infrared zenithal video take. In the first test, the UAV was followed by another positioning system simultaneously, thus allowing the comparison of both systems, and the evaluation in the improvement introduced by the particle algorithm.
publishDate 2020
dc.date.none.fl_str_mv 2020-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/289483
Comas, Edgardo Antonio; Stacul, Adrián; Delrieux, Claudio Augusto; Robust Object Tracking in Infrared Video via Particle Filters; Universitat Autònoma de Barcelona; Electronic Letters on Computer Vision and Image Analysis; 19; 1; 7-2020; 1-14
1577-5097
CONICET Digital
CONICET
url http://hdl.handle.net/11336/289483
identifier_str_mv Comas, Edgardo Antonio; Stacul, Adrián; Delrieux, Claudio Augusto; Robust Object Tracking in Infrared Video via Particle Filters; Universitat Autònoma de Barcelona; Electronic Letters on Computer Vision and Image Analysis; 19; 1; 7-2020; 1-14
1577-5097
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.5565/rev/elcvia.1185
info:eu-repo/semantics/altIdentifier/url/https://elcvia.cvc.uab.cat/article/view/v19-n1-comas
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universitat Autònoma de Barcelona
publisher.none.fl_str_mv Universitat Autònoma de Barcelona
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.24418

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