Detection and segmentation of faces using binary partition trees

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 merg...

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Detalles Bibliográficos
Autores principales:	Marqués, Ferran, Vilaplana, Verónica
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2001
Materias:	Ciencias Informáticas Segmentation Image processing software face detection face segmentation binary partition trees principal component analysis
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/23339
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-23339
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Segmentation Image processing software face detection face segmentation binary partition trees principal component analysis
spellingShingle	Ciencias Informáticas Segmentation Image processing software face detection face segmentation binary partition trees principal component analysis Marqués, Ferran Vilaplana, Verónica Detection and segmentation of faces using binary partition trees
topic_facet	Ciencias Informáticas Segmentation Image processing software face detection face segmentation binary partition trees principal component analysis
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.
format	Objeto de conferencia Objeto de conferencia
author	Marqués, Ferran Vilaplana, Verónica
author_facet	Marqués, Ferran Vilaplana, Verónica
author_sort	Marqués, Ferran
title	Detection and segmentation of faces using binary partition trees
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
publishDate	2001
url	http://sedici.unlp.edu.ar/handle/10915/23339
work_keys_str_mv	AT marquesferran detectionandsegmentationoffacesusingbinarypartitiontrees AT vilaplanaveronica detectionandsegmentationoffacesusingbinarypartitiontrees
bdutipo_str	Repositorios
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Detection and segmentation of faces using binary partition trees

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