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Descripción
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| This paper presents a novel background modeling system that uses a spatial grid of Support Vector Machines classifiers for segmenting moving objects, which is a key step in many video-based consumer applications. The system is able to adapt to a large range of dynamic background situations since no parametric model or statistical distribution are assumed. This is achieved by using a different classifier per image region that learns the specific appearance of that scene region and its variations (illumination changes, dynamic backgrounds, etc.). The proposed system has been tested with a recent public database, outperforming other state-of-the-art algorithms. | |
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Internacional
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Si |
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Nombre congreso
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IEEE Int. Conf. on Consumer Electronics, ICCE 2014 |
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Tipo de participación
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960 |
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Lugar del congreso
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Las Vegas (NV), USA |
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Revisores
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Si |
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ISBN o ISSN
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2158-3994 |
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DOI
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10.1109/ICCE.2014.6776098 |
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Fecha inicio congreso
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10/01/2014 |
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Fecha fin congreso
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13/01/2014 |
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Desde la página
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488 |
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Hasta la página
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489 |
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Título de las actas
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IEEE Int. Conf. on Consumer Electronics, ICCE 2014 |