Modelo e ferramenta para reconhecimento e classificação de gestos do corpo
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFSCAR |
Texto Completo: | https://repositorio.ufscar.br/handle/ufscar/9536 |
Resumo: | Multimodal interfaces are becoming more popular, and increasingly require natural interaction as a resource to enrich the user experience. Computational systems that support multimodality provide a more natural and flexible way to perform tasks on computers, since they allow users with different levels of skills and knowledge to choose the mode of interaction best suited to their needs. Among natural forms of interaction are the gestures, the natural interaction through gestures is becoming more popular, since it's an alternative to the conventional style of interaction based on keyboard and mouse, and also by the growth and advent of motion capture devices, with low-cost visual depth sensors. In this context, this dissertation presents a study about all the necessary steps for the construction of a model and tool for the recognition of static and dynamic gestures, these being: Segmentation; Modeling; Description; and Classification. Proposed solutions and results are presented for each of these steps and, finally, a tool that implements the model is evaluated in the recognition of gestures, using a finite set of gestures. All the solutions presented in this dissertation were encapsulated in the GGGesture tool, which aims to simplify research in the area of gesture recognition, allowing communication with multimodal interfaces systems and natural interfaces. |
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Brasil, Gustavo Jordan CastroTrevelin, Luis Carloshttp://lattes.cnpq.br/5082419783043736http://lattes.cnpq.br/678862836254658007e04e24-1879-4af1-a0f1-063a7a0e8c1b2018-03-07T11:55:46Z2018-03-07T11:55:46Z2017-08-18BRASIL, Gustavo Jordan Castro. Modelo e ferramenta para reconhecimento e classificação de gestos do corpo. 2017. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9536.https://repositorio.ufscar.br/handle/ufscar/9536Multimodal interfaces are becoming more popular, and increasingly require natural interaction as a resource to enrich the user experience. Computational systems that support multimodality provide a more natural and flexible way to perform tasks on computers, since they allow users with different levels of skills and knowledge to choose the mode of interaction best suited to their needs. Among natural forms of interaction are the gestures, the natural interaction through gestures is becoming more popular, since it's an alternative to the conventional style of interaction based on keyboard and mouse, and also by the growth and advent of motion capture devices, with low-cost visual depth sensors. In this context, this dissertation presents a study about all the necessary steps for the construction of a model and tool for the recognition of static and dynamic gestures, these being: Segmentation; Modeling; Description; and Classification. Proposed solutions and results are presented for each of these steps and, finally, a tool that implements the model is evaluated in the recognition of gestures, using a finite set of gestures. All the solutions presented in this dissertation were encapsulated in the GGGesture tool, which aims to simplify research in the area of gesture recognition, allowing communication with multimodal interfaces systems and natural interfaces.Interfaces multimodais estão cada vez mais populares, e demandam mais a interação natural como recurso para enriquecer a experiência do usuário. Sistemas computacionais que suportam a multimodalidade provêm um modo mais natural e flexível para execução de tarefas em computadores, uma vez que permitem aos usuários com diferentes níveis de habilidades e de aprendizado, escolha o modo de interação mais adequado a suas necessidades. Dentre as formas de interação natural, estão os gestos, a interação natural através de gestos vem se popularizando cada vez mais, visto que, foge do estilo convencional de interação baseado em teclado e mouse, e ainda pelo crescimento e advento de dispositivos de captura de movimento, com sensores visuais de profundidade de baixo custo. Neste contexto, esta dissertação apresenta um estudo sobre todas as etapas necessárias para a construção de um modelo e ferramenta para reconhecimento de gestos estáticos e dinâmicos, sendo estas: Segmentação; Modelagem; Descrição; e Classificação. Soluções e resultados propostos, são apresentados para cada uma destas etapas e, por fim uma ferramenta que implementa o modelo é avaliada no reconhecimento de gestos, utilizando um conjunto finito de gestos. Todas as soluções apresentadas nesta dissertação foram encapsuladas na ferramenta GGGesture, que tem por objetivo simplificar as pesquisas na área de reconhecimento de gestos, permitindo a comunicação com sistemas de interfaces multimodais e interfaces naturais.Não recebi financiamentoporUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Ciência da Computação - PPGCCUFSCarReconhecimento de gestosRealidade virtualReconhecimento de padrõesInterface naturalGesture recognitionVirtual realityPattern recognitionNatural interfaceCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOModelo e ferramenta para reconhecimento e classificação de gestos do corpoModel and tool for recognition and classification of body gesturesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisOnlinee47d05e7-5439-42fa-864a-d1da3cf4c0d6info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARLICENSElicense.txtlicense.txttext/plain; charset=utf-81957https://repositorio.ufscar.br/bitstream/ufscar/9536/4/license.txtae0398b6f8b235e40ad82cba6c50031dMD54ORIGINALBRASIL_Gustavo_2018.pdfBRASIL_Gustavo_2018.pdfapplication/pdf10017569https://repositorio.ufscar.br/bitstream/ufscar/9536/5/BRASIL_Gustavo_2018.pdf9c4cf5fa17c74194b27e89df220cd3eeMD55TEXTBRASIL_Gustavo_2018.pdf.txtBRASIL_Gustavo_2018.pdf.txtExtracted texttext/plain207258https://repositorio.ufscar.br/bitstream/ufscar/9536/6/BRASIL_Gustavo_2018.pdf.txtb401a83ad13743a1865b2320535d6deeMD56THUMBNAILBRASIL_Gustavo_2018.pdf.jpgBRASIL_Gustavo_2018.pdf.jpgIM Thumbnailimage/jpeg3843https://repositorio.ufscar.br/bitstream/ufscar/9536/7/BRASIL_Gustavo_2018.pdf.jpg864cf408968f8a0141036367d16c39c2MD57ufscar/95362023-09-18 18:31:13.845oai:repositorio.ufscar.br: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Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:13Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.por.fl_str_mv |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
dc.title.alternative.eng.fl_str_mv |
Model and tool for recognition and classification of body gestures |
title |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
spellingShingle |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo Brasil, Gustavo Jordan Castro Reconhecimento de gestos Realidade virtual Reconhecimento de padrões Interface natural Gesture recognition Virtual reality Pattern recognition Natural interface CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
title_short |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
title_full |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
title_fullStr |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
title_full_unstemmed |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
title_sort |
Modelo e ferramenta para reconhecimento e classificação de gestos do corpo |
author |
Brasil, Gustavo Jordan Castro |
author_facet |
Brasil, Gustavo Jordan Castro |
author_role |
author |
dc.contributor.authorlattes.por.fl_str_mv |
http://lattes.cnpq.br/6788628362546580 |
dc.contributor.author.fl_str_mv |
Brasil, Gustavo Jordan Castro |
dc.contributor.advisor1.fl_str_mv |
Trevelin, Luis Carlos |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/5082419783043736 |
dc.contributor.authorID.fl_str_mv |
07e04e24-1879-4af1-a0f1-063a7a0e8c1b |
contributor_str_mv |
Trevelin, Luis Carlos |
dc.subject.por.fl_str_mv |
Reconhecimento de gestos Realidade virtual Reconhecimento de padrões Interface natural |
topic |
Reconhecimento de gestos Realidade virtual Reconhecimento de padrões Interface natural Gesture recognition Virtual reality Pattern recognition Natural interface CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
dc.subject.eng.fl_str_mv |
Gesture recognition Virtual reality Pattern recognition Natural interface |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
description |
Multimodal interfaces are becoming more popular, and increasingly require natural interaction as a resource to enrich the user experience. Computational systems that support multimodality provide a more natural and flexible way to perform tasks on computers, since they allow users with different levels of skills and knowledge to choose the mode of interaction best suited to their needs. Among natural forms of interaction are the gestures, the natural interaction through gestures is becoming more popular, since it's an alternative to the conventional style of interaction based on keyboard and mouse, and also by the growth and advent of motion capture devices, with low-cost visual depth sensors. In this context, this dissertation presents a study about all the necessary steps for the construction of a model and tool for the recognition of static and dynamic gestures, these being: Segmentation; Modeling; Description; and Classification. Proposed solutions and results are presented for each of these steps and, finally, a tool that implements the model is evaluated in the recognition of gestures, using a finite set of gestures. All the solutions presented in this dissertation were encapsulated in the GGGesture tool, which aims to simplify research in the area of gesture recognition, allowing communication with multimodal interfaces systems and natural interfaces. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017-08-18 |
dc.date.accessioned.fl_str_mv |
2018-03-07T11:55:46Z |
dc.date.available.fl_str_mv |
2018-03-07T11:55:46Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
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masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
BRASIL, Gustavo Jordan Castro. Modelo e ferramenta para reconhecimento e classificação de gestos do corpo. 2017. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9536. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufscar.br/handle/ufscar/9536 |
identifier_str_mv |
BRASIL, Gustavo Jordan Castro. Modelo e ferramenta para reconhecimento e classificação de gestos do corpo. 2017. Dissertação (Mestrado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2017. Disponível em: https://repositorio.ufscar.br/handle/ufscar/9536. |
url |
https://repositorio.ufscar.br/handle/ufscar/9536 |
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por |
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por |
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openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de São Carlos Câmpus São Carlos |
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Programa de Pós-Graduação em Ciência da Computação - PPGCC |
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UFSCar |
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Universidade Federal de São Carlos Câmpus São Carlos |
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