Detection and segmentation of faces using binary partition trees

Autores
Marqués, Ferran; Vilaplana, Verónica
Año de publicación
2001
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper we improve the face detection and segmentation technique proposed in [1]. In order to obtain the shape of the face, we use a region based approach and find the face as a set of regions from a generic segmentation. The original image is segmented and a partition tree is created by merging regions from this partition. Facial descriptors and a similarity measure to faces are computed for each node. The analysis is performed using information from the regions represented by the node and also information from neighboring regions. The new method overcomes the rigidity of the tree structure and allows the extraction of new facial regions that are not represented as nodes in the tree. A search algorithm selects the nodes associated to faces. The use of information from neighboring regions significantly improves the performance of the algorithm and avoids the postprocessing step used in our previous work to completely extract the facial regions.
Eje: Programación de imágenes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Segmentation
Image processing software
face detection
face segmentation
binary partition trees
principal component analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23339

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spelling Detection and segmentation of faces using binary partition treesMarqués, FerranVilaplana, VerónicaCiencias InformáticasSegmentationImage processing softwareface detectionface segmentationbinary partition treesprincipal component analysisIn this paper we improve the face detection and segmentation technique proposed in [1]. In order to obtain the shape of the face, we use a region based approach and find the face as a set of regions from a generic segmentation. The original image is segmented and a partition tree is created by merging regions from this partition. Facial descriptors and a similarity measure to faces are computed for each node. The analysis is performed using information from the regions represented by the node and also information from neighboring regions. The new method overcomes the rigidity of the tree structure and allows the extraction of new facial regions that are not represented as nodes in the tree. A search algorithm selects the nodes associated to faces. The use of information from neighboring regions significantly improves the performance of the algorithm and avoids the postprocessing step used in our previous work to completely extract the facial regions.Eje: Programación de imágenesRed de Universidades con Carreras en Informática (RedUNCI)2001-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23339enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:25Zoai:sedici.unlp.edu.ar:10915/23339Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:25.939SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Detection and segmentation of faces using binary partition trees
title Detection and segmentation of faces using binary partition trees
spellingShingle Detection and segmentation of faces using binary partition trees
Marqués, Ferran
Ciencias Informáticas
Segmentation
Image processing software
face detection
face segmentation
binary partition trees
principal component analysis
title_short Detection and segmentation of faces using binary partition trees
title_full Detection and segmentation of faces using binary partition trees
title_fullStr Detection and segmentation of faces using binary partition trees
title_full_unstemmed Detection and segmentation of faces using binary partition trees
title_sort Detection and segmentation of faces using binary partition trees
dc.creator.none.fl_str_mv Marqués, Ferran
Vilaplana, Verónica
author Marqués, Ferran
author_facet Marqués, Ferran
Vilaplana, Verónica
author_role author
author2 Vilaplana, Verónica
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Segmentation
Image processing software
face detection
face segmentation
binary partition trees
principal component analysis
topic Ciencias Informáticas
Segmentation
Image processing software
face detection
face segmentation
binary partition trees
principal component analysis
dc.description.none.fl_txt_mv In this paper we improve the face detection and segmentation technique proposed in [1]. In order to obtain the shape of the face, we use a region based approach and find the face as a set of regions from a generic segmentation. The original image is segmented and a partition tree is created by merging regions from this partition. Facial descriptors and a similarity measure to faces are computed for each node. The analysis is performed using information from the regions represented by the node and also information from neighboring regions. The new method overcomes the rigidity of the tree structure and allows the extraction of new facial regions that are not represented as nodes in the tree. A search algorithm selects the nodes associated to faces. The use of information from neighboring regions significantly improves the performance of the algorithm and avoids the postprocessing step used in our previous work to completely extract the facial regions.
Eje: Programación de imágenes
Red de Universidades con Carreras en Informática (RedUNCI)
description In this paper we improve the face detection and segmentation technique proposed in [1]. In order to obtain the shape of the face, we use a region based approach and find the face as a set of regions from a generic segmentation. The original image is segmented and a partition tree is created by merging regions from this partition. Facial descriptors and a similarity measure to faces are computed for each node. The analysis is performed using information from the regions represented by the node and also information from neighboring regions. The new method overcomes the rigidity of the tree structure and allows the extraction of new facial regions that are not represented as nodes in the tree. A search algorithm selects the nodes associated to faces. The use of information from neighboring regions significantly improves the performance of the algorithm and avoids the postprocessing step used in our previous work to completely extract the facial regions.
publishDate 2001
dc.date.none.fl_str_mv 2001-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23339
url http://sedici.unlp.edu.ar/handle/10915/23339
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
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institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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