Bag-of-words with aggregated temporal pair-wise word co-occurrence for human action recognition
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Otros documentos de la autoría: Agustí Ballester, Pau; Traver Roig, Vicente Javier; Pla, Filiberto
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http://dx.doi.org/10.1016/j.patrec.2014.07.014 |
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Título
Bag-of-words with aggregated temporal pair-wise word co-occurrence for human action recognitionFecha de publicación
2014Editor
ElsevierISSN
0167-8655Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0167865514002311Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
The bag-of-words (BoW) representation has successfully been used for human action recognition from
videos. However, one limitation of the standard BoW is that it ignores spatial and temporal relationships
between ... [+]
The bag-of-words (BoW) representation has successfully been used for human action recognition from
videos. However, one limitation of the standard BoW is that it ignores spatial and temporal relationships
between the visual words. Although several approaches have been proposed to deal with this issue, we
propose an extension which is arguably simpler yet quite effective. The proposed representation, t-BoW,
captures only temporal relationships between pairs of words in an aggregated way by counting co-occurrences
at several temporal differences. Unlike other approaches, neither spatial nor hierarchical information
is accounted for explicitly, and no significant change is required in the quantization or classification
procedures. Performance improvements over the traditional BoW and other BoW extensions are experimentally
observed in the KTH, the ADL, the Keck, and the HMDB51 action/gestures datasets. [-]
Publicado en
Pattern Recognition Letters Volume 49, 1 November 2014, Pages 224–230Derechos de acceso
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