Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Detalhes bibliográficos
Autor(a) principal: Trigueiros, Paulo
Data de Publicação: 2015
Outros Autores: Ribeiro, A. Fernando, Reis, L. P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/39140
Resumo: Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
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spelling Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeingHuman-computer interactionGesture recognitionComputer visionMachine learningHuman-machine interactionScience & TechnologyHand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.SpringerUniversidade do MinhoTrigueiros, PauloRibeiro, A. FernandoReis, L. P.20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/39140eng0921-029610.1007/s10846-015-0192-4http://link.springer.com/article/10.1007%2Fs10846-015-0192-4info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:28:52Zoai:repositorium.sdum.uminho.pt:1822/39140Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:23:45.553118Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
title Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
spellingShingle Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
Trigueiros, Paulo
Human-computer interaction
Gesture recognition
Computer vision
Machine learning
Human-machine interaction
Science & Technology
title_short Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
title_full Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
title_fullStr Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
title_full_unstemmed Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
title_sort Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing
author Trigueiros, Paulo
author_facet Trigueiros, Paulo
Ribeiro, A. Fernando
Reis, L. P.
author_role author
author2 Ribeiro, A. Fernando
Reis, L. P.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Trigueiros, Paulo
Ribeiro, A. Fernando
Reis, L. P.
dc.subject.por.fl_str_mv Human-computer interaction
Gesture recognition
Computer vision
Machine learning
Human-machine interaction
Science & Technology
topic Human-computer interaction
Gesture recognition
Computer vision
Machine learning
Human-machine interaction
Science & Technology
description Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/39140
url http://hdl.handle.net/1822/39140
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0921-0296
10.1007/s10846-015-0192-4
http://link.springer.com/article/10.1007%2Fs10846-015-0192-4
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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