Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm

Autores
Iparraguirre, Javier; Delrieux, Claudio; Perez Meyer, Lisandro
Año de publicación
2010
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Real-time video processing is steadily becoming a standard matter in a wide diversity of applications, including computer vision, surveillance, social networks, and many other. Unsupervised video interpretation is required to avoid the operative expense and faultiness of human-in-the-loop interpretation. However, robust, general purpose real-time unsupervised video interpretation and analysis appears to be among the most difficult processing tasks. In this work we present advances in real-time video stream processing, in particular in automatic key-frames detection. This detection procedure is based on feature analysis and evaluation of the features detected by the popular SURF algorithm. We present the implementation details, some interesting experimental results are shown, and we discuss some of the applications that our detection algorithm may have.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Computer vision
video processing
robust visual descriptor
key-frame detection
parallel processing
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:10915/152721

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network_name_str SEDICI (UNLP)
spelling Automatic Real Time Key-frame Detection in Video Stream Using SURF AlgorithmIparraguirre, JavierDelrieux, ClaudioPerez Meyer, LisandroCiencias InformáticasComputer visionvideo processingrobust visual descriptorkey-frame detectionparallel processingReal-time video processing is steadily becoming a standard matter in a wide diversity of applications, including computer vision, surveillance, social networks, and many other. Unsupervised video interpretation is required to avoid the operative expense and faultiness of human-in-the-loop interpretation. However, robust, general purpose real-time unsupervised video interpretation and analysis appears to be among the most difficult processing tasks. In this work we present advances in real-time video stream processing, in particular in automatic key-frames detection. This detection procedure is based on feature analysis and evaluation of the features detected by the popular SURF algorithm. We present the implementation details, some interesting experimental results are shown, and we discuss some of the applications that our detection algorithm may have.Sociedad Argentina de Informática e Investigación Operativa2010info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1610-1613http://sedici.unlp.edu.ar/handle/10915/152721enginfo:eu-repo/semantics/altIdentifier/url/http://39jaiio.sadio.org.ar/sites/default/files/39-jaiio-ast-09.pdfinfo:eu-repo/semantics/altIdentifier/issn/1850-2806info: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:UNLP2025-09-03T11:11:24Zoai:sedici.unlp.edu.ar:10915/152721Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 11:11:24.495SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
title Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
spellingShingle Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
Iparraguirre, Javier
Ciencias Informáticas
Computer vision
video processing
robust visual descriptor
key-frame detection
parallel processing
title_short Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
title_full Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
title_fullStr Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
title_full_unstemmed Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
title_sort Automatic Real Time Key-frame Detection in Video Stream Using SURF Algorithm
dc.creator.none.fl_str_mv Iparraguirre, Javier
Delrieux, Claudio
Perez Meyer, Lisandro
author Iparraguirre, Javier
author_facet Iparraguirre, Javier
Delrieux, Claudio
Perez Meyer, Lisandro
author_role author
author2 Delrieux, Claudio
Perez Meyer, Lisandro
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Computer vision
video processing
robust visual descriptor
key-frame detection
parallel processing
topic Ciencias Informáticas
Computer vision
video processing
robust visual descriptor
key-frame detection
parallel processing
dc.description.none.fl_txt_mv Real-time video processing is steadily becoming a standard matter in a wide diversity of applications, including computer vision, surveillance, social networks, and many other. Unsupervised video interpretation is required to avoid the operative expense and faultiness of human-in-the-loop interpretation. However, robust, general purpose real-time unsupervised video interpretation and analysis appears to be among the most difficult processing tasks. In this work we present advances in real-time video stream processing, in particular in automatic key-frames detection. This detection procedure is based on feature analysis and evaluation of the features detected by the popular SURF algorithm. We present the implementation details, some interesting experimental results are shown, and we discuss some of the applications that our detection algorithm may have.
Sociedad Argentina de Informática e Investigación Operativa
description Real-time video processing is steadily becoming a standard matter in a wide diversity of applications, including computer vision, surveillance, social networks, and many other. Unsupervised video interpretation is required to avoid the operative expense and faultiness of human-in-the-loop interpretation. However, robust, general purpose real-time unsupervised video interpretation and analysis appears to be among the most difficult processing tasks. In this work we present advances in real-time video stream processing, in particular in automatic key-frames detection. This detection procedure is based on feature analysis and evaluation of the features detected by the popular SURF algorithm. We present the implementation details, some interesting experimental results are shown, and we discuss some of the applications that our detection algorithm may have.
publishDate 2010
dc.date.none.fl_str_mv 2010
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1850-2806
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
1610-1613
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instname:Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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