Efficient large-scale image search with a vocabulary tree

Autores
Uriza, Esteban; Gómez Fernández, Francisco Roberto; Rais, Martín
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The task of searching and recognizing objects in images has become an important research topic in the area of image processing and computer vision. Looking for similar images in large datasets given an input query and responding as fast as possible is a very challenging task. In this work the Bag of Features approach is studied, and an implementation of the visual vocabulary tree method from Nist´er and Stew´enius is presented. Images are described using local invariant descriptor techniques and then indexed in a database using an inverted index for further queries. The descriptors are quantized according to a visual vocabulary, creating sparse vectors, which allows to compute very efficiently, for each query, a ranking of similarity for indexed images. The performance of the method is analyzed varying different factors, such as the parameters for the vocabulary tree construction, different techniques of local descriptors extraction and dimensionality reduction with PCA. It can be observed that the retrieval performance increases with a richer vocabulary and decays very slowly as the size of the dataset grows.
Fil: Uriza, Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Gómez Fernández, Francisco Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Rais, Martín. Escuela Normal Superior de Cachan; Francia
Materia
BAG OF FEATURES
IMAGE PROCESSING
SCALABLE RECOGNITION
VOCABULARY TREE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/92344
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Efficient large-scale image search with a vocabulary treeUriza, EstebanGómez Fernández, Francisco RobertoRais, MartínBAG OF FEATURESIMAGE PROCESSINGSCALABLE RECOGNITIONVOCABULARY TREEhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The task of searching and recognizing objects in images has become an important research topic in the area of image processing and computer vision. Looking for similar images in large datasets given an input query and responding as fast as possible is a very challenging task. In this work the Bag of Features approach is studied, and an implementation of the visual vocabulary tree method from Nist´er and Stew´enius is presented. Images are described using local invariant descriptor techniques and then indexed in a database using an inverted index for further queries. The descriptors are quantized according to a visual vocabulary, creating sparse vectors, which allows to compute very efficiently, for each query, a ranking of similarity for indexed images. The performance of the method is analyzed varying different factors, such as the parameters for the vocabulary tree construction, different techniques of local descriptors extraction and dimensionality reduction with PCA. It can be observed that the retrieval performance increases with a richer vocabulary and decays very slowly as the size of the dataset grows.Fil: Uriza, Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Gómez Fernández, Francisco Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Rais, Martín. Escuela Normal Superior de Cachan; FranciaCachan2018-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/92344Uriza, Esteban; Gómez Fernández, Francisco Roberto; Rais, Martín; Efficient large-scale image search with a vocabulary tree; Cachan; Image Processing On Line; 8; 2-2018; 71-982105-1232CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.ipol.im/pub/art/2018/199/info:eu-repo/semantics/altIdentifier/doi/10.5201/ipol.2018.199info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:38:43Zoai:ri.conicet.gov.ar:11336/92344instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:38:44.204CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Efficient large-scale image search with a vocabulary tree
title Efficient large-scale image search with a vocabulary tree
spellingShingle Efficient large-scale image search with a vocabulary tree
Uriza, Esteban
BAG OF FEATURES
IMAGE PROCESSING
SCALABLE RECOGNITION
VOCABULARY TREE
title_short Efficient large-scale image search with a vocabulary tree
title_full Efficient large-scale image search with a vocabulary tree
title_fullStr Efficient large-scale image search with a vocabulary tree
title_full_unstemmed Efficient large-scale image search with a vocabulary tree
title_sort Efficient large-scale image search with a vocabulary tree
dc.creator.none.fl_str_mv Uriza, Esteban
Gómez Fernández, Francisco Roberto
Rais, Martín
author Uriza, Esteban
author_facet Uriza, Esteban
Gómez Fernández, Francisco Roberto
Rais, Martín
author_role author
author2 Gómez Fernández, Francisco Roberto
Rais, Martín
author2_role author
author
dc.subject.none.fl_str_mv BAG OF FEATURES
IMAGE PROCESSING
SCALABLE RECOGNITION
VOCABULARY TREE
topic BAG OF FEATURES
IMAGE PROCESSING
SCALABLE RECOGNITION
VOCABULARY TREE
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The task of searching and recognizing objects in images has become an important research topic in the area of image processing and computer vision. Looking for similar images in large datasets given an input query and responding as fast as possible is a very challenging task. In this work the Bag of Features approach is studied, and an implementation of the visual vocabulary tree method from Nist´er and Stew´enius is presented. Images are described using local invariant descriptor techniques and then indexed in a database using an inverted index for further queries. The descriptors are quantized according to a visual vocabulary, creating sparse vectors, which allows to compute very efficiently, for each query, a ranking of similarity for indexed images. The performance of the method is analyzed varying different factors, such as the parameters for the vocabulary tree construction, different techniques of local descriptors extraction and dimensionality reduction with PCA. It can be observed that the retrieval performance increases with a richer vocabulary and decays very slowly as the size of the dataset grows.
Fil: Uriza, Esteban. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Gómez Fernández, Francisco Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; Argentina
Fil: Rais, Martín. Escuela Normal Superior de Cachan; Francia
description The task of searching and recognizing objects in images has become an important research topic in the area of image processing and computer vision. Looking for similar images in large datasets given an input query and responding as fast as possible is a very challenging task. In this work the Bag of Features approach is studied, and an implementation of the visual vocabulary tree method from Nist´er and Stew´enius is presented. Images are described using local invariant descriptor techniques and then indexed in a database using an inverted index for further queries. The descriptors are quantized according to a visual vocabulary, creating sparse vectors, which allows to compute very efficiently, for each query, a ranking of similarity for indexed images. The performance of the method is analyzed varying different factors, such as the parameters for the vocabulary tree construction, different techniques of local descriptors extraction and dimensionality reduction with PCA. It can be observed that the retrieval performance increases with a richer vocabulary and decays very slowly as the size of the dataset grows.
publishDate 2018
dc.date.none.fl_str_mv 2018-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/92344
Uriza, Esteban; Gómez Fernández, Francisco Roberto; Rais, Martín; Efficient large-scale image search with a vocabulary tree; Cachan; Image Processing On Line; 8; 2-2018; 71-98
2105-1232
CONICET Digital
CONICET
url http://hdl.handle.net/11336/92344
identifier_str_mv Uriza, Esteban; Gómez Fernández, Francisco Roberto; Rais, Martín; Efficient large-scale image search with a vocabulary tree; Cachan; Image Processing On Line; 8; 2-2018; 71-98
2105-1232
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.ipol.im/pub/art/2018/199/
info:eu-repo/semantics/altIdentifier/doi/10.5201/ipol.2018.199
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cachan
publisher.none.fl_str_mv Cachan
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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