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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/152721
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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 |
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 |
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http://sedici.unlp.edu.ar/handle/10915/152721 |
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eng |
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eng |
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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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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