How far did we get in face spoofing detection?
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.engappai.2018.04.013 http://hdl.handle.net/11449/160335 |
Resumo: | The growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks. In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented. The analyzed works are categorized by their fundamental parts, i.e., descriptors and classifiers. This structured survey also brings a comparative performance analysis of the works considering the most important public data sets in the field. The methodology followed in this work is particularly relevant to observe temporal evolution of the field, trends in the existing approaches, to discuss still opened issues, and to propose new perspectives for the future of face spoofing detection. |
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How far did we get in face spoofing detection?Face spoofingFace recognitionSurveySpoofing attackThe growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks. In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented. The analyzed works are categorized by their fundamental parts, i.e., descriptors and classifiers. This structured survey also brings a comparative performance analysis of the works considering the most important public data sets in the field. The methodology followed in this work is particularly relevant to observe temporal evolution of the field, trends in the existing approaches, to discuss still opened issues, and to propose new perspectives for the future of face spoofing detection.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Fed Bahia, IVISION Lab, Salvador, BA, BrazilSao Paulo State Univ, RECOGNA Lab, Sao Paulo, BrazilSao Paulo State Univ, RECOGNA Lab, Sao Paulo, BrazilFAPESP: 2013/07375-0FAPESP: 2014/12236-1FAPESP: 2016/19403-6CNPq: 306166/2014-3Elsevier B.V.Universidade Federal da Bahia (UFBA)Universidade Estadual Paulista (Unesp)Souza, LuizOliveira, LucianoPamplona, MauricioPapa, Joao [UNESP]2018-11-26T16:01:25Z2018-11-26T16:01:25Z2018-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article368-381application/pdfhttp://dx.doi.org/10.1016/j.engappai.2018.04.013Engineering Applications Of Artificial Intelligence. Oxford: Pergamon-elsevier Science Ltd, v. 72, p. 368-381, 2018.0952-1976http://hdl.handle.net/11449/16033510.1016/j.engappai.2018.04.013WOS:000434239000031WOS000434239000031.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEngineering Applications Of Artificial Intelligence0,874info:eu-repo/semantics/openAccess2023-11-10T06:09:13Zoai:repositorio.unesp.br:11449/160335Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:17:21.412568Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
How far did we get in face spoofing detection? |
title |
How far did we get in face spoofing detection? |
spellingShingle |
How far did we get in face spoofing detection? Souza, Luiz Face spoofing Face recognition Survey Spoofing attack |
title_short |
How far did we get in face spoofing detection? |
title_full |
How far did we get in face spoofing detection? |
title_fullStr |
How far did we get in face spoofing detection? |
title_full_unstemmed |
How far did we get in face spoofing detection? |
title_sort |
How far did we get in face spoofing detection? |
author |
Souza, Luiz |
author_facet |
Souza, Luiz Oliveira, Luciano Pamplona, Mauricio Papa, Joao [UNESP] |
author_role |
author |
author2 |
Oliveira, Luciano Pamplona, Mauricio Papa, Joao [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal da Bahia (UFBA) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Souza, Luiz Oliveira, Luciano Pamplona, Mauricio Papa, Joao [UNESP] |
dc.subject.por.fl_str_mv |
Face spoofing Face recognition Survey Spoofing attack |
topic |
Face spoofing Face recognition Survey Spoofing attack |
description |
The growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks. In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented. The analyzed works are categorized by their fundamental parts, i.e., descriptors and classifiers. This structured survey also brings a comparative performance analysis of the works considering the most important public data sets in the field. The methodology followed in this work is particularly relevant to observe temporal evolution of the field, trends in the existing approaches, to discuss still opened issues, and to propose new perspectives for the future of face spoofing detection. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-11-26T16:01:25Z 2018-11-26T16:01:25Z 2018-06-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.engappai.2018.04.013 Engineering Applications Of Artificial Intelligence. Oxford: Pergamon-elsevier Science Ltd, v. 72, p. 368-381, 2018. 0952-1976 http://hdl.handle.net/11449/160335 10.1016/j.engappai.2018.04.013 WOS:000434239000031 WOS000434239000031.pdf |
url |
http://dx.doi.org/10.1016/j.engappai.2018.04.013 http://hdl.handle.net/11449/160335 |
identifier_str_mv |
Engineering Applications Of Artificial Intelligence. Oxford: Pergamon-elsevier Science Ltd, v. 72, p. 368-381, 2018. 0952-1976 10.1016/j.engappai.2018.04.013 WOS:000434239000031 WOS000434239000031.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Engineering Applications Of Artificial Intelligence 0,874 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
368-381 application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128785180000256 |