Video Surveillance for Road Traffic Monitoring

Autores
Torres, Guillermo; Caminal, Iván; Maldonado, Cristina; Górriz, Marc
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This work proposes a framework for road traffic surveillance using computer vision techniques. After a foreground estimation, post processing techniques are applied to the detected vehicles in motion to generate blobs. Then, a tracking approach based on Kalman filters is used to extract instantaneous information throughout a video sequence, including speed and trajectory estimation and imprudent driving detection. The system has been developed in Python and can be launched in real-time using a standard CPU. The code is available at github: https://github.com/mcv-m6-video/mcv-m6-2018-team3.
XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
traffic control
road monitoring
foreground segmentation
vehicle tracking
kalman filter
speed estimator
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/73214
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/73214
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Video Surveillance for Road Traffic MonitoringTorres, GuillermoCaminal, IvánMaldonado, CristinaGórriz, MarcCiencias Informáticastraffic controlroad monitoringforeground segmentationvehicle trackingkalman filterspeed estimatorThis work proposes a framework for road traffic surveillance using computer vision techniques. After a foreground estimation, post processing techniques are applied to the detected vehicles in motion to generate blobs. Then, a tracking approach based on Kalman filters is used to extract instantaneous information throughout a video sequence, including speed and trajectory estimation and imprudent driving detection. The system has been developed in Python and can be launched in real-time using a standard CPU. The code is available at github: https://github.com/mcv-m6-video/mcv-m6-2018-team3.XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI)2018-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf412-421http://sedici.unlp.edu.ar/handle/10915/73214enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-10T12:15:05Zoai:sedici.unlp.edu.ar:10915/73214Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 12:15:05.278SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Video Surveillance for Road Traffic Monitoring
title Video Surveillance for Road Traffic Monitoring
spellingShingle Video Surveillance for Road Traffic Monitoring
Torres, Guillermo
Ciencias Informáticas
traffic control
road monitoring
foreground segmentation
vehicle tracking
kalman filter
speed estimator
title_short Video Surveillance for Road Traffic Monitoring
title_full Video Surveillance for Road Traffic Monitoring
title_fullStr Video Surveillance for Road Traffic Monitoring
title_full_unstemmed Video Surveillance for Road Traffic Monitoring
title_sort Video Surveillance for Road Traffic Monitoring
dc.creator.none.fl_str_mv Torres, Guillermo
Caminal, Iván
Maldonado, Cristina
Górriz, Marc
author Torres, Guillermo
author_facet Torres, Guillermo
Caminal, Iván
Maldonado, Cristina
Górriz, Marc
author_role author
author2 Caminal, Iván
Maldonado, Cristina
Górriz, Marc
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
traffic control
road monitoring
foreground segmentation
vehicle tracking
kalman filter
speed estimator
topic Ciencias Informáticas
traffic control
road monitoring
foreground segmentation
vehicle tracking
kalman filter
speed estimator
dc.description.none.fl_txt_mv This work proposes a framework for road traffic surveillance using computer vision techniques. After a foreground estimation, post processing techniques are applied to the detected vehicles in motion to generate blobs. Then, a tracking approach based on Kalman filters is used to extract instantaneous information throughout a video sequence, including speed and trajectory estimation and imprudent driving detection. The system has been developed in Python and can be launched in real-time using a standard CPU. The code is available at github: https://github.com/mcv-m6-video/mcv-m6-2018-team3.
XVI Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)
Red de Universidades con Carreras en Informática (RedUNCI)
description This work proposes a framework for road traffic surveillance using computer vision techniques. After a foreground estimation, post processing techniques are applied to the detected vehicles in motion to generate blobs. Then, a tracking approach based on Kalman filters is used to extract instantaneous information throughout a video sequence, including speed and trajectory estimation and imprudent driving detection. The system has been developed in Python and can be launched in real-time using a standard CPU. The code is available at github: https://github.com/mcv-m6-video/mcv-m6-2018-team3.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/73214
url http://sedici.unlp.edu.ar/handle/10915/73214
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
412-421
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 12.993085

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