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High-quality region-based foreground segmentation using a spatial grid of SVM classifiers
Cita
Zhang, Xiaohan, Blanco Adán, Carlos Roberto del 
ORCID: https://orcid.org/0000-0003-0618-3488, Cuevas Rodríguez, Carlos ORCID: https://orcid.org/0000-0001-9873-8502, Jaureguizar Núñez, Fernando ORCID: https://orcid.org/0000-0001-6449-5151 and García Santos, Narciso ORCID: https://orcid.org/0000-0002-0397-894X
(2014).
High-quality region-based foreground segmentation using a spatial grid of SVM classifiers.
En: "IEEE International Conference on Consumer Electronics (ICCE 2014)", 10/01/2014 - 13/01/2014, Las Vegas, Nevada, USA. pp. 488-489.
ORCID: https://orcid.org/0000-0003-0618-3488, Cuevas Rodríguez, Carlos ORCID: https://orcid.org/0000-0001-9873-8502, Jaureguizar Núñez, Fernando ORCID: https://orcid.org/0000-0001-6449-5151 and García Santos, Narciso ORCID: https://orcid.org/0000-0002-0397-894X
(2014).
High-quality region-based foreground segmentation using a spatial grid of SVM classifiers.
En: "IEEE International Conference on Consumer Electronics (ICCE 2014)", 10/01/2014 - 13/01/2014, Las Vegas, Nevada, USA. pp. 488-489.
Descripción
| Título: | High-quality region-based foreground segmentation using a spatial grid of SVM classifiers |
|---|---|
| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | IEEE International Conference on Consumer Electronics (ICCE 2014) |
| Fechas del Evento: | 10/01/2014 - 13/01/2014 |
| Lugar del Evento: | Las Vegas, Nevada, USA |
| Título del Libro: | IEEE International Conference on Consumer Electronics (ICCE 2014) |
| Título de Revista/Publicación: | 2014 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE) |
| Fecha: | 2014 |
| ISSN: | 2158-3994 |
| Número: | null |
| Materias: | |
| ODS: | |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Señales, Sistemas y Radiocomunicaciones |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
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.
Más información
| ID de Registro: | 36202 |
|---|---|
| Identificador DC: | https://oa.upm.es/36202/ |
| Identificador OAI: | oai:oa.upm.es:36202 |
| URL Oficial: | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb... |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 04 Jul 2015 07:46 |
| Ultima Modificación: | 04 Jul 2015 07:46 |
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