A new video segmentation method of moving objects based on blob-level knowledge

Carmona, Enrique J., Martínez Campos, Javier y Mira, José . (2008) A new video segmentation method of moving objects based on blob-level knowledge. Pattern Recognition Letters 29(3), 272-285 (2008)

Ficheros (Some files may be inaccessible until you login with your e-spacio credentials)
Nombre Descripción Tipo MIME Size
Carmona_Suarez_Enrique_VIDEO_SEGMENTATION.pdf Carmona_Suarez_Enrique_VIDEO_SEGMENTATION.pdf application/pdf 2.15MB

Título A new video segmentation method of moving objects based on blob-level knowledge
Autor(es) Carmona, Enrique J.
Martínez Campos, Javier
Mira, José
Materia(s) Informática
Ingeniería Informática
Abstract Variants of the background subtraction method are broadly used for the detection of moving objects in video sequences in different applications. In this work we propose a new approach to the background subtraction method which operates in the colour space and manages the colour information in the segmentation process to detect and eliminate noise. This new method is combined with blob-level knowledge associated with different types of blobs that may appear in the foreground. The idea is to process each pixel differently according to the category to which it belongs: real moving objects, shadows, ghosts, reflections, fluctuation or background noise. Thus, the foreground resulting from processing each image frame is refined selectively, applying at each instant the appropriate operator according to the type of noise blob we wish to eliminate. The approach proposed is adaptive, because it allows both the background model and threshold model to be updated. On the one hand, the results obtained confirm the robustness of the method proposed in a wide range of different sequences and, on the other hand, these results underline the importance of handling three colour components in the segmentation process rather than just the one grey-level component.
Palabras clave Background subtraction
reflection detection
shadow detection
ghost detection
permanence memory
blob-level knowledge
Editor(es) Elsevier
Fecha 2008-02-01
Formato application/pdf
Identificador bibliuned:95-Ejcarmona-0017
http://e-spacio.uned.es/fez/view/bibliuned:95-Ejcarmona-0017
DOI - identifier http://dx.doi.org/10.1016/j.patrec.2007.10.007
ISSN - identifier 0167-8655
Nombre de la revista Pattern Recognition Letters
Número de Volumen 29
Número de Issue 3
Página inicial 272
Página final 285
Publicado en la Revista Pattern Recognition Letters 29(3), 272-285 (2008)
Idioma eng
Versión de la publicación acceptedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto
Notas adicionales This is an Accepted Manuscript of an article published by Elsevier in "Pattern Recognition Letters 29(3), 272-285 (2008)", available at: http://dx.doi.org/10.1016/j.patrec.2007.10.007
Notas adicionales Este es el manuscrito aceptado del artículo publicado por Elsevier en "Pattern Recognition Letters 29(3), 272-285 (2008)", disponible en: http://dx.doi.org/10.1016/j.patrec.2007.10.007

 
Versiones
Versión Tipo de filtro
Contador de citas: Google Scholar Search Google Scholar
Estadísticas de acceso: 47 Visitas, 10 Descargas  -  Estadísticas en detalle
Creado: Thu, 11 Apr 2024, 18:34:46 CET