Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost

This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms...

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Autores:
Tipo de recurso:
Article of journal
Fecha de publicación:
2013
Institución:
Universidad Antonio Nariño
Repositorio:
Repositorio UAN
Idioma:
spa
OAI Identifier:
oai:repositorio.uan.edu.co:123456789/10426
Acceso en línea:
https://revistas.uan.edu.co/index.php/ingeuan/article/view/348
https://repositorio.uan.edu.co/handle/123456789/10426
Palabra clave:
AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
Rights
License
https://creativecommons.org/licenses/by-nc-sa/4.0
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oai_identifier_str oai:repositorio.uan.edu.co:123456789/10426
network_acronym_str UAntonioN2
network_name_str Repositorio UAN
repository_id_str
spelling 2013-09-092024-10-10T02:24:50Z2024-10-10T02:24:50Zhttps://revistas.uan.edu.co/index.php/ingeuan/article/view/348https://repositorio.uan.edu.co/handle/123456789/10426This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms performances are remarkable and therefore its use could have a positive impact in the reduction of traffic problems.Este artículo presenta el diseño e implementación y comparación de algoritmos para la clasificación de vehículos privados y públicos en Bogotá. El desempeño de estos algoritmos de clasificación es notable, y vale la pena anotar el impacto potencial que tendrían en la reducción de problemas de tráfico. Los datos experimentales fueron imágenes segmentadas de vídeos tomados sobre el tráfico en la ciudad de Bogotá. Por otro lado, los algoritmos que se utilizaron son máquinas de aprendizaje como Support Vector Machines “SVM” y Adaboost. Vale la pena notar, que se hizo uso de las librerías OpenCV implementadas en C.application/pdfspaUNIVERSIDAD ANTONIO NARIÑOhttps://revistas.uan.edu.co/index.php/ingeuan/article/view/348/290https://creativecommons.org/licenses/by-nc-sa/4.0http://purl.org/coar/access_right/c_abf2INGE@UAN - TENDENCIAS EN LA INGENIERÍA; Vol. 3 Núm. 5 (2012)2346-14462145-0935AdaBosstárboles binariosOpenCVreconocimiento de patronesSVMIngeniería de tráficoclasificación de vehículosAdaBoostBinary TreesOpenCVPattern recognitionSVMTraffic engineeringVehicles classificationPublic And Private Service Vehicle Classification In Bogotá using SVM and AdaBoostinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Calderon, FranciscoParra, Carlos Alberto123456789/10426oai:repositorio.uan.edu.co:123456789/104262024-10-14 03:47:34.166metadata.onlyhttps://repositorio.uan.edu.coRepositorio Institucional UANalertas.repositorio@uan.edu.co
dc.title.es-ES.fl_str_mv Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
spellingShingle Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
title_short Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_full Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_fullStr Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_full_unstemmed Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
title_sort Public And Private Service Vehicle Classification In Bogotá using SVM and AdaBoost
dc.subject.es-ES.fl_str_mv AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
topic AdaBosst
árboles binarios
OpenCV
reconocimiento de patrones
SVM
Ingeniería de tráfico
clasificación de vehículos
AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
dc.subject.en-US.fl_str_mv AdaBoost
Binary Trees
OpenCV
Pattern recognition
SVM
Traffic engineering
Vehicles classification
description This paper presents the implementation and comparison of algorithms for support vector machines “SVM” and AdaBoost in the classification of public and private vehicles using segmented images of video sequences taken in Bogotá city. Using as tools the OpenCV libraries implemented in C. The algorithms performances are remarkable and therefore its use could have a positive impact in the reduction of traffic problems.
publishDate 2013
dc.date.accessioned.none.fl_str_mv 2024-10-10T02:24:50Z
dc.date.available.none.fl_str_mv 2024-10-10T02:24:50Z
dc.date.none.fl_str_mv 2013-09-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coarversion.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uan.edu.co/index.php/ingeuan/article/view/348
dc.identifier.uri.none.fl_str_mv https://repositorio.uan.edu.co/handle/123456789/10426
url https://revistas.uan.edu.co/index.php/ingeuan/article/view/348
https://repositorio.uan.edu.co/handle/123456789/10426
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistas.uan.edu.co/index.php/ingeuan/article/view/348/290
dc.rights.es-ES.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0
http://purl.org/coar/access_right/c_abf2
dc.format.none.fl_str_mv application/pdf
dc.publisher.es-ES.fl_str_mv UNIVERSIDAD ANTONIO NARIÑO
dc.source.es-ES.fl_str_mv INGE@UAN - TENDENCIAS EN LA INGENIERÍA; Vol. 3 Núm. 5 (2012)
dc.source.none.fl_str_mv 2346-1446
2145-0935
institution Universidad Antonio Nariño
repository.name.fl_str_mv Repositorio Institucional UAN
repository.mail.fl_str_mv alertas.repositorio@uan.edu.co
_version_ 1814300293097062400

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