Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields

Autores
Manera, José F.; Vainstein, Jonathan; Delrieux, Claudio; Maguitman, Ana Gabriela
Año de publicación
2013
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The aim of Action Recognition is the automated analysis and interpretation of events in video sequences. As result of the applications that can be developed, and the widespread availability and popularization of digital video (security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as video security, humancomputer interaction, patient monitoring and video retrieval, among others. Our long-term goal is to develop automatic action identification in video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
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:10915/76861
Acceder
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network_name_str SEDICI (UNLP)
spelling Action Recognition in Tennis Videos using Optical Flow and Conditional Random FieldsManera, José F.Vainstein, JonathanDelrieux, ClaudioMaguitman, Ana GabrielaCiencias Informáticasaction recognitionconditional random fieldsoptical flowTrackingThe aim of Action Recognition is the automated analysis and interpretation of events in video sequences. As result of the applications that can be developed, and the widespread availability and popularization of digital video (security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as video security, humancomputer interaction, patient monitoring and video retrieval, among others. Our long-term goal is to develop automatic action identification in video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.Sociedad Argentina de Informática e Investigación Operativa2013-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf152-162http://sedici.unlp.edu.ar/handle/10915/76861enginfo:eu-repo/semantics/altIdentifier/url/http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/AST/14.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:UNLP2025-09-29T11:13:39Zoai:sedici.unlp.edu.ar:10915/76861Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:13:39.333SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
title Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
spellingShingle Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
Manera, José F.
Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
title_short Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
title_full Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
title_fullStr Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
title_full_unstemmed Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
title_sort Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
dc.creator.none.fl_str_mv Manera, José F.
Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
author Manera, José F.
author_facet Manera, José F.
Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
author_role author
author2 Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
topic Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
dc.description.none.fl_txt_mv The aim of Action Recognition is the automated analysis and interpretation of events in video sequences. As result of the applications that can be developed, and the widespread availability and popularization of digital video (security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as video security, humancomputer interaction, patient monitoring and video retrieval, among others. Our long-term goal is to develop automatic action identification in video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.
Sociedad Argentina de Informática e Investigación Operativa
description The aim of Action Recognition is the automated analysis and interpretation of events in video sequences. As result of the applications that can be developed, and the widespread availability and popularization of digital video (security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as video security, humancomputer interaction, patient monitoring and video retrieval, among others. Our long-term goal is to develop automatic action identification in video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.
publishDate 2013
dc.date.none.fl_str_mv 2013-09
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info:eu-repo/semantics/publishedVersion
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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/10915/76861
url http://sedici.unlp.edu.ar/handle/10915/76861
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
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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
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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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