3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1145/2695664.2695807 http://hdl.handle.net/11449/177738 |
Resumo: | Pose and illumination variability are two major problems with 2D face recognition. Since 3D data is less sensible to illumination changes and can be used to adjust pose variations, it has been adopted to improve performance on face recognition systems. The main problem with utilizing 3D data is the high cost of the traditional 3D scanners. The Kinect is a low cost device that can be used to obtain the 3D data from an environment in a fast manner, but with lower accuracy than the traditional scanners. Recently, a 3D Local Binary Pattern (3DLBP) method was proposed for 3D face recognition by using high resolution scanners. The main goal of this work is to assess the performance of 3DLBP method, fused with Histogram of Averaged Oriented Gradients (HAOG) face descriptor method, for face recognition when Kinect is used as the 3D face scanner. Another goal is to compare the 3DLBP method, fused with HAOG descriptor, with other methods proposed in the literature for face recognition by using Kinect. Experimental results on EURECOM face dataset showed that the data generated by Kinect are discriminative enough to allow face recognition and that 3DLBP performs better than the other methods. Copyright is held by the owner/author(s). |
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Repositório Institucional da UNESP |
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spelling |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner3D face recognition3DLBPHAOGKinectPose and illumination variability are two major problems with 2D face recognition. Since 3D data is less sensible to illumination changes and can be used to adjust pose variations, it has been adopted to improve performance on face recognition systems. The main problem with utilizing 3D data is the high cost of the traditional 3D scanners. The Kinect is a low cost device that can be used to obtain the 3D data from an environment in a fast manner, but with lower accuracy than the traditional scanners. Recently, a 3D Local Binary Pattern (3DLBP) method was proposed for 3D face recognition by using high resolution scanners. The main goal of this work is to assess the performance of 3DLBP method, fused with Histogram of Averaged Oriented Gradients (HAOG) face descriptor method, for face recognition when Kinect is used as the 3D face scanner. Another goal is to compare the 3DLBP method, fused with HAOG descriptor, with other methods proposed in the literature for face recognition by using Kinect. Experimental results on EURECOM face dataset showed that the data generated by Kinect are discriminative enough to allow face recognition and that 3DLBP performs better than the other methods. Copyright is held by the owner/author(s).Graduate Program in Computer Science UNESP - São Paulo State UniversityDepartment of Computing Faculty of Sciences UNESP - São Paulo State UniversityGraduate Program in Computer Science UNESP - São Paulo State UniversityDepartment of Computing Faculty of Sciences UNESP - São Paulo State UniversityUniversidade Estadual Paulista (Unesp)Cardia Neto, João Baptista [UNESP]Marana, Aparecido Nilceu [UNESP]2018-12-11T17:26:53Z2018-12-11T17:26:53Z2015-04-13info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject66-73http://dx.doi.org/10.1145/2695664.2695807Proceedings of the ACM Symposium on Applied Computing, v. 13-17-April-2015, p. 66-73.http://hdl.handle.net/11449/17773810.1145/2695664.26958072-s2.0-84955478290Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of the ACM Symposium on Applied Computinginfo:eu-repo/semantics/openAccess2024-04-23T16:11:27Zoai:repositorio.unesp.br:11449/177738Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:20:19.482753Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
title |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
spellingShingle |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner Cardia Neto, João Baptista [UNESP] 3D face recognition 3DLBP HAOG Kinect |
title_short |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
title_full |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
title_fullStr |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
title_full_unstemmed |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
title_sort |
3DLBP and HAOG fusion for face recognition utilizing kinect as a 3D scanner |
author |
Cardia Neto, João Baptista [UNESP] |
author_facet |
Cardia Neto, João Baptista [UNESP] Marana, Aparecido Nilceu [UNESP] |
author_role |
author |
author2 |
Marana, Aparecido Nilceu [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Cardia Neto, João Baptista [UNESP] Marana, Aparecido Nilceu [UNESP] |
dc.subject.por.fl_str_mv |
3D face recognition 3DLBP HAOG Kinect |
topic |
3D face recognition 3DLBP HAOG Kinect |
description |
Pose and illumination variability are two major problems with 2D face recognition. Since 3D data is less sensible to illumination changes and can be used to adjust pose variations, it has been adopted to improve performance on face recognition systems. The main problem with utilizing 3D data is the high cost of the traditional 3D scanners. The Kinect is a low cost device that can be used to obtain the 3D data from an environment in a fast manner, but with lower accuracy than the traditional scanners. Recently, a 3D Local Binary Pattern (3DLBP) method was proposed for 3D face recognition by using high resolution scanners. The main goal of this work is to assess the performance of 3DLBP method, fused with Histogram of Averaged Oriented Gradients (HAOG) face descriptor method, for face recognition when Kinect is used as the 3D face scanner. Another goal is to compare the 3DLBP method, fused with HAOG descriptor, with other methods proposed in the literature for face recognition by using Kinect. Experimental results on EURECOM face dataset showed that the data generated by Kinect are discriminative enough to allow face recognition and that 3DLBP performs better than the other methods. Copyright is held by the owner/author(s). |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-04-13 2018-12-11T17:26:53Z 2018-12-11T17:26:53Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1145/2695664.2695807 Proceedings of the ACM Symposium on Applied Computing, v. 13-17-April-2015, p. 66-73. http://hdl.handle.net/11449/177738 10.1145/2695664.2695807 2-s2.0-84955478290 |
url |
http://dx.doi.org/10.1145/2695664.2695807 http://hdl.handle.net/11449/177738 |
identifier_str_mv |
Proceedings of the ACM Symposium on Applied Computing, v. 13-17-April-2015, p. 66-73. 10.1145/2695664.2695807 2-s2.0-84955478290 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings of the ACM Symposium on Applied Computing |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
66-73 |
dc.source.none.fl_str_mv |
Scopus 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_ |
1808129311104827392 |