Estudo dimensional de características aplicadas à leitura labial automática
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFS |
Texto Completo: | http://ri.ufs.br/jspui/handle/riufs/9567 |
Resumo: | This work is a study of the relationship between the intrinsic dimension of feature vectors applied to the classification of video signals in order to perform lip reading. In pattern recognition tasks, the extraction of relevant features is crucial for a good performance of the classifiers. The starting point of this work was the reproduction of the work of J.R. Movellan [1], which classifies lips gestures with HMM using only the video signal from the Tulips1 database. The database consists of videos of volunteers’ mouths while they utter the first 4 numerals in English. The original work uses feature vectors of high dimensionality in relation to the size of the database. Consequently, the adjustment of HMM classifiers has become problematic and the maximum accuracy was only 66.67%. Alternative strategies for feature extraction and classification schemes were proposed in order to analyze the influence of the intrinsic dimension in the performance of classifiers. The best solution, in terms of results, achieved an accuracy of approximately 83%. |
id |
UFS-2_bafe5ec2999f18403c8cf8fc8e3f5532 |
---|---|
oai_identifier_str |
oai:ufs.br:riufs/9567 |
network_acronym_str |
UFS-2 |
network_name_str |
Repositório Institucional da UFS |
repository_id_str |
|
spelling |
Madureira, Fillipe Levi GuedesMontalvão Filho, Jugurta Rosa2018-11-06T19:24:06Z2018-11-06T19:24:06Z2018-08-31MADUREIRA, Fillipe Levi Guedes. Estudo dimensional de características aplicadas à leitura labial automática. 2018. 64 f. Dissertação (Mestrado em Engenharia Elétrica)–Universidade Federal de Sergipe, São Cristóvão, SE, 2018.http://ri.ufs.br/jspui/handle/riufs/9567This work is a study of the relationship between the intrinsic dimension of feature vectors applied to the classification of video signals in order to perform lip reading. In pattern recognition tasks, the extraction of relevant features is crucial for a good performance of the classifiers. The starting point of this work was the reproduction of the work of J.R. Movellan [1], which classifies lips gestures with HMM using only the video signal from the Tulips1 database. The database consists of videos of volunteers’ mouths while they utter the first 4 numerals in English. The original work uses feature vectors of high dimensionality in relation to the size of the database. Consequently, the adjustment of HMM classifiers has become problematic and the maximum accuracy was only 66.67%. Alternative strategies for feature extraction and classification schemes were proposed in order to analyze the influence of the intrinsic dimension in the performance of classifiers. The best solution, in terms of results, achieved an accuracy of approximately 83%.Este trabalho é um estudo da relação entre a dimensão intrínseca de vetores de características aplicados à classificação de sinais de vídeo no intuito de realizar-se a leitura labial. Nas tarefas de reconhecimento de padrões, a extração de características relevantes é crucial para um bom desempenho dos classificadores. O ponto de partida deste trabalho foi a reprodução do trabalho de J.R. Movellan [1], que realiza a classificação de gestos labiais com HMM na base de dados Tulips1, utilizando somente o sinal de vídeo. A base é composta por vídeos das bocas de voluntários enquanto esses pronunciam os primeiros 4 numerais em inglês. O trabalho original utiliza vetores de características de dimensão muito alta em relação ao tamanho da base. Consequentemente, o ajuste de classificadores HMM se tornou problemático e só se alcançou 66,67% de acurácia. Estratégias de extração de características e esquemas de classificação alternativos foram propostos, a fim de analisar a influência da dimensão intrínseca no desempenho de classificadores. A melhor solução, em termos de resultados, obteve uma acurácia de aproximadamente 83%.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESSão Cristóvão, SEporEngenharia elétricaSurdosComunicação oralSistemas de reconhecimento de padrõesDimensão intrínsecaExtração de característicasLeitura labialHidden Markov Model (HMM)Intrinsic dimensionFeature extractionLip-readingENGENHARIAS::ENGENHARIA ELETRICAEstudo dimensional de características aplicadas à leitura labial automáticainfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPós-Graduação em Engenharia ElétricaUFSreponame:Repositório Institucional da UFSinstname:Universidade Federal de Sergipe (UFS)instacron:UFSinfo:eu-repo/semantics/openAccessTEXTFILLIPE_LEVI_GUEDES_MADUREIRA.pdf.txtFILLIPE_LEVI_GUEDES_MADUREIRA.pdf.txtExtracted texttext/plain132976https://ri.ufs.br/jspui/bitstream/riufs/9567/3/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf.txt2fadbc77dcf0bd14b20f268ab50850aeMD53THUMBNAILFILLIPE_LEVI_GUEDES_MADUREIRA.pdf.jpgFILLIPE_LEVI_GUEDES_MADUREIRA.pdf.jpgGenerated Thumbnailimage/jpeg1510https://ri.ufs.br/jspui/bitstream/riufs/9567/4/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf.jpgc69e73216071e8339e4dcade12c57e02MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81475https://ri.ufs.br/jspui/bitstream/riufs/9567/1/license.txt098cbbf65c2c15e1fb2e49c5d306a44cMD51ORIGINALFILLIPE_LEVI_GUEDES_MADUREIRA.pdfFILLIPE_LEVI_GUEDES_MADUREIRA.pdfapplication/pdf1490616https://ri.ufs.br/jspui/bitstream/riufs/9567/2/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf3604d87a7edc5c01970026f502ba8791MD52riufs/95672018-11-06 16:24:06.583oai:ufs.br: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Repositório InstitucionalPUBhttps://ri.ufs.br/oai/requestrepositorio@academico.ufs.bropendoar:2018-11-06T19:24:06Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS)false |
dc.title.pt_BR.fl_str_mv |
Estudo dimensional de características aplicadas à leitura labial automática |
title |
Estudo dimensional de características aplicadas à leitura labial automática |
spellingShingle |
Estudo dimensional de características aplicadas à leitura labial automática Madureira, Fillipe Levi Guedes Engenharia elétrica Surdos Comunicação oral Sistemas de reconhecimento de padrões Dimensão intrínseca Extração de características Leitura labial Hidden Markov Model (HMM) Intrinsic dimension Feature extraction Lip-reading ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Estudo dimensional de características aplicadas à leitura labial automática |
title_full |
Estudo dimensional de características aplicadas à leitura labial automática |
title_fullStr |
Estudo dimensional de características aplicadas à leitura labial automática |
title_full_unstemmed |
Estudo dimensional de características aplicadas à leitura labial automática |
title_sort |
Estudo dimensional de características aplicadas à leitura labial automática |
author |
Madureira, Fillipe Levi Guedes |
author_facet |
Madureira, Fillipe Levi Guedes |
author_role |
author |
dc.contributor.author.fl_str_mv |
Madureira, Fillipe Levi Guedes |
dc.contributor.advisor1.fl_str_mv |
Montalvão Filho, Jugurta Rosa |
contributor_str_mv |
Montalvão Filho, Jugurta Rosa |
dc.subject.por.fl_str_mv |
Engenharia elétrica Surdos Comunicação oral Sistemas de reconhecimento de padrões Dimensão intrínseca Extração de características Leitura labial Hidden Markov Model (HMM) |
topic |
Engenharia elétrica Surdos Comunicação oral Sistemas de reconhecimento de padrões Dimensão intrínseca Extração de características Leitura labial Hidden Markov Model (HMM) Intrinsic dimension Feature extraction Lip-reading ENGENHARIAS::ENGENHARIA ELETRICA |
dc.subject.eng.fl_str_mv |
Intrinsic dimension Feature extraction Lip-reading |
dc.subject.cnpq.fl_str_mv |
ENGENHARIAS::ENGENHARIA ELETRICA |
description |
This work is a study of the relationship between the intrinsic dimension of feature vectors applied to the classification of video signals in order to perform lip reading. In pattern recognition tasks, the extraction of relevant features is crucial for a good performance of the classifiers. The starting point of this work was the reproduction of the work of J.R. Movellan [1], which classifies lips gestures with HMM using only the video signal from the Tulips1 database. The database consists of videos of volunteers’ mouths while they utter the first 4 numerals in English. The original work uses feature vectors of high dimensionality in relation to the size of the database. Consequently, the adjustment of HMM classifiers has become problematic and the maximum accuracy was only 66.67%. Alternative strategies for feature extraction and classification schemes were proposed in order to analyze the influence of the intrinsic dimension in the performance of classifiers. The best solution, in terms of results, achieved an accuracy of approximately 83%. |
publishDate |
2018 |
dc.date.accessioned.fl_str_mv |
2018-11-06T19:24:06Z |
dc.date.available.fl_str_mv |
2018-11-06T19:24:06Z |
dc.date.issued.fl_str_mv |
2018-08-31 |
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.citation.fl_str_mv |
MADUREIRA, Fillipe Levi Guedes. Estudo dimensional de características aplicadas à leitura labial automática. 2018. 64 f. Dissertação (Mestrado em Engenharia Elétrica)–Universidade Federal de Sergipe, São Cristóvão, SE, 2018. |
dc.identifier.uri.fl_str_mv |
http://ri.ufs.br/jspui/handle/riufs/9567 |
identifier_str_mv |
MADUREIRA, Fillipe Levi Guedes. Estudo dimensional de características aplicadas à leitura labial automática. 2018. 64 f. Dissertação (Mestrado em Engenharia Elétrica)–Universidade Federal de Sergipe, São Cristóvão, SE, 2018. |
url |
http://ri.ufs.br/jspui/handle/riufs/9567 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.program.fl_str_mv |
Pós-Graduação em Engenharia Elétrica |
dc.publisher.initials.fl_str_mv |
UFS |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFS instname:Universidade Federal de Sergipe (UFS) instacron:UFS |
instname_str |
Universidade Federal de Sergipe (UFS) |
instacron_str |
UFS |
institution |
UFS |
reponame_str |
Repositório Institucional da UFS |
collection |
Repositório Institucional da UFS |
bitstream.url.fl_str_mv |
https://ri.ufs.br/jspui/bitstream/riufs/9567/3/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf.txt https://ri.ufs.br/jspui/bitstream/riufs/9567/4/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf.jpg https://ri.ufs.br/jspui/bitstream/riufs/9567/1/license.txt https://ri.ufs.br/jspui/bitstream/riufs/9567/2/FILLIPE_LEVI_GUEDES_MADUREIRA.pdf |
bitstream.checksum.fl_str_mv |
2fadbc77dcf0bd14b20f268ab50850ae c69e73216071e8339e4dcade12c57e02 098cbbf65c2c15e1fb2e49c5d306a44c 3604d87a7edc5c01970026f502ba8791 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS) |
repository.mail.fl_str_mv |
repositorio@academico.ufs.br |
_version_ |
1802110812717842432 |