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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23339
Ver los metadatos del registro completo
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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 Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/23339 |
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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 |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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application/pdf |
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