Reconhecimento de faces 3D com Kinect
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/127666 http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/31-08-2015/000844097.pdf |
Resumo: | For person identification, facil recognition has several advantages over other biometric traits due mostly to its high universelly, collectability, and acceptability. When dealing with 2D face images several problems arise related to pose, illumination, and facial expressions. To increase the performance of facial recognition, 3D mehtods have been proposed and developedm since working with 3D objects allow us to handle better the aforementioned problems. With 3D object, it is possible to rotate the face around any axis, generate illumination that matches the one in the enviroment and even correct the deformation in the model due to facial expression. The mais problems with 3D facial recognition are: the high cost of the 3D cameras that have been generally employed, and intrusive way that such devices work. Some of them require that the subject remais completely still for several minutes while scanning, limiting, therefpre, the application deployment for uncontrollable enviroments. One alternative to those expensive cameras is the Kinect, a device developed by Microsoft to enchance gaming in the Xbok 360 console. Due to its capacites to generate depth images, Kinect is candidate device to be use for 3D face recognition, replacing the traditional 3D cameras. The mais problem with the Kinect is that it generates low-resolution images, making difficult the ask of precise facial recognition. The mais objective of this dissertation was to ptoposed some mehtods that have been proposed recently for 3D face recognition and to propose a neu method that combines 3DLBP and HAOG features. Experimental results obtained on the EURECOM 3D face database show that when 3DLBP and HAOG features are combineted the results can be better than they are used alone. We Have also proposed a method that increase the facial recognition performance when the faces present partial obstructions, by utilizing a symetric filling approach |
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Reconhecimento de faces 3D com KinectComputaçãoProcessamento de imagens - Tecnicas digitaisReconhecimento facial (Computação)BiometriaImagem tridimensionalSistemas imageadoresFor person identification, facil recognition has several advantages over other biometric traits due mostly to its high universelly, collectability, and acceptability. When dealing with 2D face images several problems arise related to pose, illumination, and facial expressions. To increase the performance of facial recognition, 3D mehtods have been proposed and developedm since working with 3D objects allow us to handle better the aforementioned problems. With 3D object, it is possible to rotate the face around any axis, generate illumination that matches the one in the enviroment and even correct the deformation in the model due to facial expression. The mais problems with 3D facial recognition are: the high cost of the 3D cameras that have been generally employed, and intrusive way that such devices work. Some of them require that the subject remais completely still for several minutes while scanning, limiting, therefpre, the application deployment for uncontrollable enviroments. One alternative to those expensive cameras is the Kinect, a device developed by Microsoft to enchance gaming in the Xbok 360 console. Due to its capacites to generate depth images, Kinect is candidate device to be use for 3D face recognition, replacing the traditional 3D cameras. The mais problem with the Kinect is that it generates low-resolution images, making difficult the ask of precise facial recognition. The mais objective of this dissertation was to ptoposed some mehtods that have been proposed recently for 3D face recognition and to propose a neu method that combines 3DLBP and HAOG features. Experimental results obtained on the EURECOM 3D face database show that when 3DLBP and HAOG features are combineted the results can be better than they are used alone. We Have also proposed a method that increase the facial recognition performance when the faces present partial obstructions, by utilizing a symetric filling approachPara identificação de pessoas o reconhecimento facila possui várias vantagens sobre outros tipos de biometria, principalmente por sua alta universalidade, coletabilidade e aceitabilidade. Quando lidando com reconhecimento de faces 2D vários probelmas aparecem normalmente relacionaos com pose, iluminação e espressão facial. Para aumentar a performance de métodos de reconhecimento facial vários algoritmos que utilizam modelos 3D foram propostos, uma vez que esse tipo de dado permite maios facilidade para tratamento dos problemas já mencionados. Com um modelo 3D é possível rotacionar a face em qualquer eixo, projetar iluminação e corrigir deformações ocasionadas por expressão. Os maiores problemas com reconhecimento de faces 3D são vinculados com seus scanners, o alto custo e a forma intrusiva que eles funcionam. Alguns scanners 3D necessitam que a pessoa fique parada por todo o tempo de captura do modelo e, portanto, limitado a sua aplicação. Uma alternativa para scanners 3D tradicionais é a utilização do Kinect, um dispositivo criado pela Microsoft para aumentar a interação dos usuários com jogos no Xbox 360. O maior problema com o Kinect é que ele gera imagens de baixa resolução, dificultando a utilização desses dados para o reconhecimento de faces 3D. O principal objetivo dessa dissertação é analisar alguns métodos que foram propostos para o reconhecimento de faces 3D e propor novas formas de realizar essa função utilizando os dados do Kinect, com isso propromos um método que combina os descritores 3DLBP e o HAOG. Resultados experimentais obtidos no database EURECOM 3D mostraam que a fusão dos métodos melhora o desempenho de ambos. Também foram propostas formas de melhorar a qualidade das faces quando houver obstrução parcial da face usando preenchimento simétricoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Estadual Paulista (Unesp)Marana, Aparecido Nilceu [UNESP]Universidade Estadual Paulista (Unesp)Cardia Neto, João Baptista [UNESP]2015-09-17T15:24:52Z2015-09-17T15:24:52Z2014-12-18info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis64 f. : il., gráfs. tabs. color.application/pdfCARDIA NETO, João Baptista. Reconhecimento de faces 3D com Kinect. 2014. 64 f. Dissertação (mestrado) - Universidade Estadual Paulista Julio de Mesquita Filho, Instituto de Biociências, Letras e Ciências Exatas, 2014.http://hdl.handle.net/11449/127666000844097http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/31-08-2015/000844097.pdf33004153073P2Alephreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPenginfo:eu-repo/semantics/openAccess2023-10-24T06:11:45Zoai:repositorio.unesp.br:11449/127666Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:50:32.349616Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Reconhecimento de faces 3D com Kinect |
title |
Reconhecimento de faces 3D com Kinect |
spellingShingle |
Reconhecimento de faces 3D com Kinect Cardia Neto, João Baptista [UNESP] Computação Processamento de imagens - Tecnicas digitais Reconhecimento facial (Computação) Biometria Imagem tridimensional Sistemas imageadores |
title_short |
Reconhecimento de faces 3D com Kinect |
title_full |
Reconhecimento de faces 3D com Kinect |
title_fullStr |
Reconhecimento de faces 3D com Kinect |
title_full_unstemmed |
Reconhecimento de faces 3D com Kinect |
title_sort |
Reconhecimento de faces 3D com Kinect |
author |
Cardia Neto, João Baptista [UNESP] |
author_facet |
Cardia Neto, João Baptista [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Marana, Aparecido Nilceu [UNESP] Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Cardia Neto, João Baptista [UNESP] |
dc.subject.por.fl_str_mv |
Computação Processamento de imagens - Tecnicas digitais Reconhecimento facial (Computação) Biometria Imagem tridimensional Sistemas imageadores |
topic |
Computação Processamento de imagens - Tecnicas digitais Reconhecimento facial (Computação) Biometria Imagem tridimensional Sistemas imageadores |
description |
For person identification, facil recognition has several advantages over other biometric traits due mostly to its high universelly, collectability, and acceptability. When dealing with 2D face images several problems arise related to pose, illumination, and facial expressions. To increase the performance of facial recognition, 3D mehtods have been proposed and developedm since working with 3D objects allow us to handle better the aforementioned problems. With 3D object, it is possible to rotate the face around any axis, generate illumination that matches the one in the enviroment and even correct the deformation in the model due to facial expression. The mais problems with 3D facial recognition are: the high cost of the 3D cameras that have been generally employed, and intrusive way that such devices work. Some of them require that the subject remais completely still for several minutes while scanning, limiting, therefpre, the application deployment for uncontrollable enviroments. One alternative to those expensive cameras is the Kinect, a device developed by Microsoft to enchance gaming in the Xbok 360 console. Due to its capacites to generate depth images, Kinect is candidate device to be use for 3D face recognition, replacing the traditional 3D cameras. The mais problem with the Kinect is that it generates low-resolution images, making difficult the ask of precise facial recognition. The mais objective of this dissertation was to ptoposed some mehtods that have been proposed recently for 3D face recognition and to propose a neu method that combines 3DLBP and HAOG features. Experimental results obtained on the EURECOM 3D face database show that when 3DLBP and HAOG features are combineted the results can be better than they are used alone. We Have also proposed a method that increase the facial recognition performance when the faces present partial obstructions, by utilizing a symetric filling approach |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-12-18 2015-09-17T15:24:52Z 2015-09-17T15:24:52Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
CARDIA NETO, João Baptista. Reconhecimento de faces 3D com Kinect. 2014. 64 f. Dissertação (mestrado) - Universidade Estadual Paulista Julio de Mesquita Filho, Instituto de Biociências, Letras e Ciências Exatas, 2014. http://hdl.handle.net/11449/127666 000844097 http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/31-08-2015/000844097.pdf 33004153073P2 |
identifier_str_mv |
CARDIA NETO, João Baptista. Reconhecimento de faces 3D com Kinect. 2014. 64 f. Dissertação (mestrado) - Universidade Estadual Paulista Julio de Mesquita Filho, Instituto de Biociências, Letras e Ciências Exatas, 2014. 000844097 33004153073P2 |
url |
http://hdl.handle.net/11449/127666 http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/31-08-2015/000844097.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
64 f. : il., gráfs. tabs. color. application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
publisher.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.source.none.fl_str_mv |
Aleph 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_ |
1808128572754231296 |