Face detection on real low resolution surveillance videos

Descripción del Articulo

This research was supported by CIENCIACTIVA, CONCYTEC and the National University of San Agustin (UNSA). We thank all professors who collaborate in the research.
Detalles Bibliográficos
Autores: Cardenas R.J.T., Castañón C.A.B., Cáceres J.C.G.
Formato: objeto de conferencia
Fecha de Publicación:2018
Institución:Consejo Nacional de Ciencia Tecnología e Innovación
Repositorio:CONCYTEC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.concytec.gob.pe:20.500.12390/561
Enlace del recurso:https://hdl.handle.net/20.500.12390/561
https://doi.org/10.1145/3193077.3193084
Nivel de acceso:acceso abierto
Materia:Security systems
Data handling
Information analysis
Optical flows
https://purl.org/pe-repo/ocde/ford#1.02.00
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oai_identifier_str oai:repositorio.concytec.gob.pe:20.500.12390/561
network_acronym_str CONC
network_name_str CONCYTEC-Institucional
repository_id_str 4689
dc.title.none.fl_str_mv Face detection on real low resolution surveillance videos
title Face detection on real low resolution surveillance videos
spellingShingle Face detection on real low resolution surveillance videos
Cardenas R.J.T.
Security systems
Data handling
Information analysis
Optical flows
https://purl.org/pe-repo/ocde/ford#1.02.00
title_short Face detection on real low resolution surveillance videos
title_full Face detection on real low resolution surveillance videos
title_fullStr Face detection on real low resolution surveillance videos
title_full_unstemmed Face detection on real low resolution surveillance videos
title_sort Face detection on real low resolution surveillance videos
author Cardenas R.J.T.
author_facet Cardenas R.J.T.
Castañón C.A.B.
Cáceres J.C.G.
author_role author
author2 Castañón C.A.B.
Cáceres J.C.G.
author2_role author
author
dc.contributor.author.fl_str_mv Cardenas R.J.T.
Castañón C.A.B.
Cáceres J.C.G.
dc.subject.none.fl_str_mv Security systems
topic Security systems
Data handling
Information analysis
Optical flows
https://purl.org/pe-repo/ocde/ford#1.02.00
dc.subject.es_PE.fl_str_mv Data handling
Information analysis
Optical flows
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#1.02.00
description This research was supported by CIENCIACTIVA, CONCYTEC and the National University of San Agustin (UNSA). We thank all professors who collaborate in the research.
publishDate 2018
dc.date.accessioned.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.available.none.fl_str_mv 2024-05-30T23:13:38Z
dc.date.issued.fl_str_mv 2018
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
dc.identifier.isbn.none.fl_str_mv urn:isbn:9781450363594
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12390/561
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1145/3193077.3193084
dc.identifier.scopus.none.fl_str_mv 2-s2.0-85048319786
identifier_str_mv urn:isbn:9781450363594
2-s2.0-85048319786
url https://hdl.handle.net/20.500.12390/561
https://doi.org/10.1145/3193077.3193084
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv ACM International Conference Proceeding Series
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Association for Computing Machinery
publisher.none.fl_str_mv Association for Computing Machinery
dc.source.none.fl_str_mv reponame:CONCYTEC-Institucional
instname:Consejo Nacional de Ciencia Tecnología e Innovación
instacron:CONCYTEC
instname_str Consejo Nacional de Ciencia Tecnología e Innovación
instacron_str CONCYTEC
institution CONCYTEC
reponame_str CONCYTEC-Institucional
collection CONCYTEC-Institucional
repository.name.fl_str_mv Repositorio Institucional CONCYTEC
repository.mail.fl_str_mv repositorio@concytec.gob.pe
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spelling Publicationrp01012600rp01013600rp00687500Cardenas R.J.T.Castañón C.A.B.Cáceres J.C.G.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2018urn:isbn:9781450363594https://hdl.handle.net/20.500.12390/561https://doi.org/10.1145/3193077.31930842-s2.0-85048319786This research was supported by CIENCIACTIVA, CONCYTEC and the National University of San Agustin (UNSA). We thank all professors who collaborate in the research.The use of video cameras for security reasons has increased in recent times. Identify a person with automatic face detection systems have greater importance today; but the low-quality of the videos make it difficult and are still an open problem that many researchers are trying to solve. We propose a novel methodology for face detection on low-resolution videos based on parallel Gunnar Farnebäck optical flow algorithm, Haar Cascades and Local Binary Patterns. Our model does not use illumination normalization or super-resolution techniques, commonly used in literature. The results on the Caviar Database prove a better detection rate compared with OpenCv Library, Dlib C++ Library and Matlab function, which use the known Viola-Jones Haar cascade algorithm and HOGs. Even though these tools not have a number of detections up to 1%, our proposal can detect faces in a rate of 50%.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengAssociation for Computing MachineryACM International Conference Proceeding Seriesinfo:eu-repo/semantics/openAccessSecurity systemsData handling-1Information analysis-1Optical flows-1https://purl.org/pe-repo/ocde/ford#1.02.00-1Face detection on real low resolution surveillance videosinfo:eu-repo/semantics/conferenceObjectreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/561oai:repositorio.concytec.gob.pe:20.500.12390/5612024-05-30 15:58:00.566http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="26cc86c4-18ca-4df7-8bf1-e1de16d55058"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Face detection on real low resolution surveillance videos</Title> <PublishedIn> <Publication> <Title>ACM International Conference Proceeding Series</Title> </Publication> </PublishedIn> <PublicationDate>2018</PublicationDate> <DOI>https://doi.org/10.1145/3193077.3193084</DOI> <SCP-Number>2-s2.0-85048319786</SCP-Number> <ISBN>urn:isbn:9781450363594</ISBN> <Authors> <Author> <DisplayName>Cardenas R.J.T.</DisplayName> <Person id="rp01012" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Castañón C.A.B.</DisplayName> <Person id="rp01013" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Cáceres J.C.G.</DisplayName> <Person id="rp00687" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Association for Computing Machinery</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>Security systems</Keyword> <Keyword>Data handling</Keyword> <Keyword>Information analysis</Keyword> <Keyword>Optical flows</Keyword> <Abstract>The use of video cameras for security reasons has increased in recent times. Identify a person with automatic face detection systems have greater importance today; but the low-quality of the videos make it difficult and are still an open problem that many researchers are trying to solve. We propose a novel methodology for face detection on low-resolution videos based on parallel Gunnar Farnebäck optical flow algorithm, Haar Cascades and Local Binary Patterns. Our model does not use illumination normalization or super-resolution techniques, commonly used in literature. The results on the Caviar Database prove a better detection rate compared with OpenCv Library, Dlib C++ Library and Matlab function, which use the known Viola-Jones Haar cascade algorithm and HOGs. Even though these tools not have a number of detections up to 1%, our proposal can detect faces in a rate of 50%.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1
score 13.08006
Face detection on real low resolution surveillance videos
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

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