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Abstract:

Video and image classification based on Instance-to-Class (I2C) distance attracted many recent studies, due to the good generalization capabilities it provides for non-parametric classifiers. In this work we propose a method for action recognition. Our approach needs no intensive learning stage, and its classification performance is comparable to the state-of-the-art. A smart organization of training data allows the classifier to achieve reasonable computation times when working with large training databases. An efficient method for organizing training data in such a way is proposed. We perform thorough experiments on two popular action recognition datasets: the KTH dataset and the IXMAS dataset, and we study the influence of one of the key parameters of the method on classification performance. © 2013 Elsevier B.V. All rights reserved.

Registro:

Documento: Artículo
Título:Efficient descriptor tree growing for fast action recognition
Autor:Ubalde, S.; Goussies, N.A.; Mejail, M.E.
Filiación:Departamento de Computation, Facultad de Ciencias Exactes y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
Palabras clave:Action recognition; Instance-to-Class distance; Nearest neighbor; Pattern recognition; Software engineering; Action recognition; Class-distance; Classification performance; Generalization capability; Nearest neighbors; Non-parametric classifiers; State of the art; Training database; Classification (of information)
Año:2014
Volumen:36
Número:1
Página de inicio:213
Página de fin:220
DOI: http://dx.doi.org/10.1016/j.patrec.2013.05.007
Título revista:Pattern Recognition Letters
Título revista abreviado:Pattern Recogn. Lett.
ISSN:01678655
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v36_n1_p213_Ubalde

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Citas:

---------- APA ----------
Ubalde, S., Goussies, N.A. & Mejail, M.E. (2014) . Efficient descriptor tree growing for fast action recognition. Pattern Recognition Letters, 36(1), 213-220.
http://dx.doi.org/10.1016/j.patrec.2013.05.007
---------- CHICAGO ----------
Ubalde, S., Goussies, N.A., Mejail, M.E. "Efficient descriptor tree growing for fast action recognition" . Pattern Recognition Letters 36, no. 1 (2014) : 213-220.
http://dx.doi.org/10.1016/j.patrec.2013.05.007
---------- MLA ----------
Ubalde, S., Goussies, N.A., Mejail, M.E. "Efficient descriptor tree growing for fast action recognition" . Pattern Recognition Letters, vol. 36, no. 1, 2014, pp. 213-220.
http://dx.doi.org/10.1016/j.patrec.2013.05.007
---------- VANCOUVER ----------
Ubalde, S., Goussies, N.A., Mejail, M.E. Efficient descriptor tree growing for fast action recognition. Pattern Recogn. Lett. 2014;36(1):213-220.
http://dx.doi.org/10.1016/j.patrec.2013.05.007