Fuzzy approach for data association in image tracking

A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all in...

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Detalles Bibliográficos
Autores: García, Jesús, Molina, José Manuel, Besada, Juan Alberto, Portillo García, Javier Ignacio
Tipo de recurso: artículo
Fecha de publicación:2003
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/1741
Acceso en línea:https://hdl.handle.net/2099/1741
Access Level:acceso abierto
Palabra clave:Image tracking
Fuzzy systems
Blobs
A-SMGCS sueveillance function
Processament electrònic de dades en temps real
Imatges -- Processament -- Tècniques digitals -- Models matemàtics
Visió artificial (Robòtica)
Lògica difusa
Classificació AMS::68 Computer science::68U Computing methodologies and applications
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oai_identifier_str oai:upcommons.upc.edu:2099/1741
network_acronym_str ES
network_name_str España
repository_id_str
spelling Fuzzy approach for data association in image trackingGarcía, JesúsMolina, José ManuelBesada, Juan AlbertoPortillo García, Javier IgnacioImage trackingFuzzy systemsBlobsA-SMGCS sueveillance functionProcessament electrònic de dades en temps realImatges -- Processament -- Tècniques digitals -- Models matemàticsVisió artificial (Robòtica)Lògica difusaClassificació AMS::68 Computer science::68U Computing methodologies and applicationsA fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs to tracks to estimate the number of targets in the scenario and their parameters. The system was initially built with a set of rules derived from performance analysis, and then a procedure based on neuro-fuzzy techniques was applied to automatically obtain rules from examples. A validation of learned system shows its capability to produce appropriate decisions. Results obtained with real data in representative ground operations show the system capabilities to solve complex scenarios and improve tracking accuracy.Peer ReviewedUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica20032003-01-0120062006-05-31journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2099/1741reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099/17412026-05-27T15:37:01Z
dc.title.none.fl_str_mv Fuzzy approach for data association in image tracking
title Fuzzy approach for data association in image tracking
spellingShingle Fuzzy approach for data association in image tracking
García, Jesús
Image tracking
Fuzzy systems
Blobs
A-SMGCS sueveillance function
Processament electrònic de dades en temps real
Imatges -- Processament -- Tècniques digitals -- Models matemàtics
Visió artificial (Robòtica)
Lògica difusa
Classificació AMS::68 Computer science::68U Computing methodologies and applications
title_short Fuzzy approach for data association in image tracking
title_full Fuzzy approach for data association in image tracking
title_fullStr Fuzzy approach for data association in image tracking
title_full_unstemmed Fuzzy approach for data association in image tracking
title_sort Fuzzy approach for data association in image tracking
dc.creator.none.fl_str_mv García, Jesús
Molina, José Manuel
Besada, Juan Alberto
Portillo García, Javier Ignacio
author García, Jesús
author_facet García, Jesús
Molina, José Manuel
Besada, Juan Alberto
Portillo García, Javier Ignacio
author_role author
author2 Molina, José Manuel
Besada, Juan Alberto
Portillo García, Javier Ignacio
author2_role author
author
author
dc.subject.none.fl_str_mv Image tracking
Fuzzy systems
Blobs
A-SMGCS sueveillance function
Processament electrònic de dades en temps real
Imatges -- Processament -- Tècniques digitals -- Models matemàtics
Visió artificial (Robòtica)
Lògica difusa
Classificació AMS::68 Computer science::68U Computing methodologies and applications
topic Image tracking
Fuzzy systems
Blobs
A-SMGCS sueveillance function
Processament electrònic de dades en temps real
Imatges -- Processament -- Tècniques digitals -- Models matemàtics
Visió artificial (Robòtica)
Lògica difusa
Classificació AMS::68 Computer science::68U Computing methodologies and applications
description A fuzzy system has been developed to ponder update decisions both for the trajectories and shapes estimated for targets. It is embedded in an A-SMGCS Surveillance function for airport surface, based on video data processing, in charge of the automatic detection, identification and tracking of all interesting targets (aircraft and relevant ground vehicles). The tracking system captures a sequence of images, preprocesses them to extract the moving regions (blobs), and associates the blobs to tracks to estimate the number of targets in the scenario and their parameters. The system was initially built with a set of rules derived from performance analysis, and then a procedure based on neuro-fuzzy techniques was applied to automatically obtain rules from examples. A validation of learned system shows its capability to produce appropriate decisions. Results obtained with real data in representative ground operations show the system capabilities to solve complex scenarios and improve tracking accuracy.
publishDate 2003
dc.date.none.fl_str_mv 2003
2003-01-01
2006
2006-05-31
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099/1741
url https://hdl.handle.net/2099/1741
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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