Face recognition using SIFT descriptors and binary PSO with velocity control

Autores
Maulini, Juan Andrés; Lanzarini, Laura Cristina
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper, a strategy for face recognition based on SIFT descriptors of the images involved is presented. In order to reduce the number of false positives and computation time, a selection of the most representative feature descriptors is carried out by applying a variation of the binary PSO method. This version improves its operation by a suitable positioning of the velocity vector. To achieve this, a new modified version of the continuous gBest PSO algorithm is used. The results obtained allow stating that the descriptors can be successfully selected through the strategy proposed solving the problems initially mentioned.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
face recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity control
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:10915/18622
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/18622
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Face recognition using SIFT descriptors and binary PSO with velocity controlMaulini, Juan AndrésLanzarini, Laura CristinaCiencias Informáticasface recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity controlIn this paper, a strategy for face recognition based on SIFT descriptors of the images involved is presented. In order to reduce the number of false positives and computation time, a selection of the most representative feature descriptors is carried out by applying a variation of the binary PSO method. This version improves its operation by a suitable positioning of the velocity vector. To achieve this, a new modified version of the continuous gBest PSO algorithm is used. The results obtained allow stating that the descriptors can be successfully selected through the strategy proposed solving the problems initially mentioned.Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2011-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf111-120http://sedici.unlp.edu.ar/handle/10915/18622enginfo: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:UNLP2025-09-29T10:53:36Zoai:sedici.unlp.edu.ar:10915/18622Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:53:36.522SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Face recognition using SIFT descriptors and binary PSO with velocity control
title Face recognition using SIFT descriptors and binary PSO with velocity control
spellingShingle Face recognition using SIFT descriptors and binary PSO with velocity control
Maulini, Juan Andrés
Ciencias Informáticas
face recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity control
title_short Face recognition using SIFT descriptors and binary PSO with velocity control
title_full Face recognition using SIFT descriptors and binary PSO with velocity control
title_fullStr Face recognition using SIFT descriptors and binary PSO with velocity control
title_full_unstemmed Face recognition using SIFT descriptors and binary PSO with velocity control
title_sort Face recognition using SIFT descriptors and binary PSO with velocity control
dc.creator.none.fl_str_mv Maulini, Juan Andrés
Lanzarini, Laura Cristina
author Maulini, Juan Andrés
author_facet Maulini, Juan Andrés
Lanzarini, Laura Cristina
author_role author
author2 Lanzarini, Laura Cristina
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
face recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity control
topic Ciencias Informáticas
face recognition; SIFT descriptors; swarm intelligence; binary PSO; velocity control
dc.description.none.fl_txt_mv In this paper, a strategy for face recognition based on SIFT descriptors of the images involved is presented. In order to reduce the number of false positives and computation time, a selection of the most representative feature descriptors is carried out by applying a variation of the binary PSO method. This version improves its operation by a suitable positioning of the velocity vector. To achieve this, a new modified version of the continuous gBest PSO algorithm is used. The results obtained allow stating that the descriptors can be successfully selected through the strategy proposed solving the problems initially mentioned.
Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description In this paper, a strategy for face recognition based on SIFT descriptors of the images involved is presented. In order to reduce the number of false positives and computation time, a selection of the most representative feature descriptors is carried out by applying a variation of the binary PSO method. This version improves its operation by a suitable positioning of the velocity vector. To achieve this, a new modified version of the continuous gBest PSO algorithm is used. The results obtained allow stating that the descriptors can be successfully selected through the strategy proposed solving the problems initially mentioned.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
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/10915/18622
url http://sedici.unlp.edu.ar/handle/10915/18622
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
111-120
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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