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Segmentation-tracking feedback approach for high-performance video surveillance applications
Cita
Cuevas Rodríguez, Carlos 
ORCID: https://orcid.org/0000-0001-9873-8502, Blanco Adán, Carlos Roberto del ORCID: https://orcid.org/0000-0003-0618-3488, García Santos, Narciso ORCID: https://orcid.org/0000-0002-0397-894X and Jaureguizar Núñez, Fernando ORCID: https://orcid.org/0000-0001-6449-5151
(2010).
Segmentation-tracking feedback approach for high-performance video surveillance applications.
En: "IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)", 23-25 de Mayo del 2010, Austin, Tejas, EEUU. ISBN 978-1-4244-7801-9.
ORCID: https://orcid.org/0000-0001-9873-8502, Blanco Adán, Carlos Roberto del ORCID: https://orcid.org/0000-0003-0618-3488, García Santos, Narciso ORCID: https://orcid.org/0000-0002-0397-894X and Jaureguizar Núñez, Fernando ORCID: https://orcid.org/0000-0001-6449-5151
(2010).
Segmentation-tracking feedback approach for high-performance video surveillance applications.
En: "IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI)", 23-25 de Mayo del 2010, Austin, Tejas, EEUU. ISBN 978-1-4244-7801-9.
Descripción
| Título: | Segmentation-tracking feedback approach for high-performance video surveillance applications |
|---|---|
| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI) |
| Fechas del Evento: | 23-25 de Mayo del 2010 |
| Lugar del Evento: | Austin, Tejas, EEUU |
| Título del Libro: | IEEE Southwest Symposium on Image Analysis & Interpretation (SSIAI) |
| Fecha: | 14 Junio 2010 |
| ISBN: | 978-1-4244-7801-9 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Bayesian methods , Computer vision , Feedback , Image segmentation , Lighting , Object detection , Object segmentation , Predictive models , Video sequences , Video surveillance |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Señales, Sistemas y Radiocomunicaciones |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
Resumen
Here, a novel and efficient feedback system for moving object segmentation and tracking is proposed. Through the use of non-parametric background-foreground modeling, moving objects are correctly detected in unfavorable situations such as dynamic backgrounds or illumination changes. After detection, objects are tracked by an original multi-object Bayesian tracking algorithm, which achieves satisfactory results under partial and total occlusions. Updating the previously detected foreground data from the information provided by the tracker, the foreground modeling is improved, reducing the color similarity problem.
Más información
| ID de Registro: | 7269 |
|---|---|
| Identificador DC: | https://oa.upm.es/7269/ |
| Identificador OAI: | oai:oa.upm.es:7269 |
| URL Oficial: | http://ieeexplore.ieee.org/search/srchabstract.jsp... |
| Depositado por: | Doctor Carlos Roberto del Blanco Adán |
| Depositado el: | 27 May 2011 11:48 |
| Ultima Modificación: | 20 Abr 2016 16:27 |
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