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

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 ar...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Manera, José F., Vainstein, Jonathan, Delrieux, Claudio, Maguitman, Ana Gabriela
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2013
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/76861
http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/AST/14.pdf
Aporte de:
id I19-R120-10915-76861
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
spellingShingle Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
Manera, José F.
Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
topic_facet Ciencias Informáticas
action recognition
conditional random fields
optical flow
Tracking
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.
format Objeto de conferencia
Objeto de conferencia
author Manera, José F.
Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
author_facet Manera, José F.
Vainstein, Jonathan
Delrieux, Claudio
Maguitman, Ana Gabriela
author_sort Manera, José F.
title Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
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
publishDate 2013
url http://sedici.unlp.edu.ar/handle/10915/76861
http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/AST/14.pdf
work_keys_str_mv AT manerajosef actionrecognitionintennisvideosusingopticalflowandconditionalrandomfields
AT vainsteinjonathan actionrecognitionintennisvideosusingopticalflowandconditionalrandomfields
AT delrieuxclaudio actionrecognitionintennisvideosusingopticalflowandconditionalrandomfields
AT maguitmananagabriela actionrecognitionintennisvideosusingopticalflowandconditionalrandomfields
bdutipo_str Repositorios
_version_ 1764820484750311425