ATM-based analysis and recognition of handball team activities
Impacto
Scholar |
Otros documentos de la autoría: Montoliu Colás, Raul; Martín Félez, Raúl; Torres-Sospedra, Joaquín; Rodríguez Pérez, Sergio
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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http://dx.doi.org/10.1016/j.neucom.2014.09.053 |
Metadatos
Título
ATM-based analysis and recognition of handball team activitiesFecha de publicación
2015Editor
ElsevierISSN
0925-2312Cita bibliográfica
MONTOLIU, Raúl, et al. ATM-based analysis and recognition of handball team activities. Neurocomputing, 2015, vol. 150, Part A, p. 189-199.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0925231214012600Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
In this paper, a new methodology based on the Author Topic Model (ATM) method is presented to perform team activity recognition and analysis in handball videos. Instead of using players׳ trajectories we just rely on ... [+]
In this paper, a new methodology based on the Author Topic Model (ATM) method is presented to perform team activity recognition and analysis in handball videos. Instead of using players׳ trajectories we just rely on low level features related to local motion, the evolution of which is then modeled over time by the ATM. The proposed methodology is applied to the task of recognizing four kinds of team activities in handball videos from the CVBASE׳06 dataset and to analyze which are the most important elements of the activities. Our method is compared with two other ways of characterizing videos based on Bag-of-Words (BoW) and Latent Dirichlet Allocation (LDA) techniques. Our proposal obtains competitive results in terms of accuracy, computing time and interpretation of the results. [-]
Publicado en
Neurocomputing, 2015, vol. 150, Part ADerechos de acceso
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/restrictedAccess
info:eu-repo/semantics/restrictedAccess
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