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Interfaces gestuais baseados no controlador Leap Motion

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Resumo:In the present, most of the human-machine interactions are based on the use of peripherals such as keyboard and computer mouse. However, the use of such peripherals can create certain limitations in the way people interact with machines, for this reason, there is a need to create natural interfaces. One of the possible approaches that has been proposed involves performing gestures that are recognized by a sensor and interpreted by the computer. The use of hands on a human-machine interface is justified by the fact that the hands are an important element in nonverbal communications. Due to this, in this project several possible gesture interfaces were analyzed, using the Leap Motion sensor. The project was based on the development of methods that allowed the recognition of gestures and their association to an action that the computer should perform. Through the analysis of existing studies in the area and the various methods used to allow a program to classify a data set, a gesture classification system was developed. The classification system has tested to verify its accuracy and precision. Using the knowledge obtained throughout the project, and as proof of concept, an application was developed to demonstrate the usefulness of the classification system in a real situation. This application can recognize a gesture and associate it with a keyboard key, allowing a user to write the message resulting from the gestures he makes. This project main conclusion was that the gesture classification system trained using SVM can make a good separation of the various gestures and with this classify correctly the gestures. Most of problems that arise during the recognition of a gesture are a consequence of the Leap Motion not being able to track correctly the gesture being made.
Autores principais:Bizarro, João Pedro Pereira
Assunto:Leap motion Hand gesture Gesture interfaces Gesture classification Classification system Motion sensor
Ano:2019
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Coimbra
Idioma:português
Origem:Instituto Politécnico de Coimbra
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author Bizarro, João Pedro Pereira
author_facet Bizarro, João Pedro Pereira
author_role author
contributor_name_str_mv Martins, Nuno Alexandre Cid
Paredes, Simão Pedro Mendes Cruz Reis
Repositório Comum
country_str PT
creators_json_txt [{\"Person.name\":\"Bizarro, João Pedro Pereira\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Martins, Nuno Alexandre Cid
Paredes, Simão Pedro Mendes Cruz Reis
Repositório Comum
datacite.creators.creator.creatorName.fl_str_mv Bizarro, João Pedro Pereira
datacite.date.Accepted.fl_str_mv 2019-06-24T00:00:00Z
datacite.date.available.fl_str_mv 2021-05-10T11:12:18Z
datacite.date.embargoed.fl_str_mv 2021-05-10T11:12:18Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
datacite.titles.title.fl_str_mv Interfaces gestuais baseados no controlador Leap Motion
dc.contributor.none.fl_str_mv Martins, Nuno Alexandre Cid
Paredes, Simão Pedro Mendes Cruz Reis
Repositório Comum
dc.creator.none.fl_str_mv Bizarro, João Pedro Pereira
dc.date.Accepted.fl_str_mv 2019-06-24T00:00:00Z
dc.date.available.fl_str_mv 2021-05-10T11:12:18Z
dc.date.embargoed.fl_str_mv 2021-05-10T11:12:18Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10400.26/36452
dc.language.none.fl_str_mv por
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
dc.title.fl_str_mv Interfaces gestuais baseados no controlador Leap Motion
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_bdcc
description In the present, most of the human-machine interactions are based on the use of peripherals such as keyboard and computer mouse. However, the use of such peripherals can create certain limitations in the way people interact with machines, for this reason, there is a need to create natural interfaces. One of the possible approaches that has been proposed involves performing gestures that are recognized by a sensor and interpreted by the computer. The use of hands on a human-machine interface is justified by the fact that the hands are an important element in nonverbal communications. Due to this, in this project several possible gesture interfaces were analyzed, using the Leap Motion sensor. The project was based on the development of methods that allowed the recognition of gestures and their association to an action that the computer should perform. Through the analysis of existing studies in the area and the various methods used to allow a program to classify a data set, a gesture classification system was developed. The classification system has tested to verify its accuracy and precision. Using the knowledge obtained throughout the project, and as proof of concept, an application was developed to demonstrate the usefulness of the classification system in a real situation. This application can recognize a gesture and associate it with a keyboard key, allowing a user to write the message resulting from the gestures he makes. This project main conclusion was that the gesture classification system trained using SVM can make a good separation of the various gestures and with this classify correctly the gestures. Most of problems that arise during the recognition of a gesture are a consequence of the Leap Motion not being able to track correctly the gesture being made.
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person_str_mv Bizarro, João Pedro Pereira
publishDate 2019
reponame_str Instituto Politécnico de Coimbra
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spelling porpt_PTIn the present, most of the human-machine interactions are based on the use of peripherals such as keyboard and computer mouse. However, the use of such peripherals can create certain limitations in the way people interact with machines, for this reason, there is a need to create natural interfaces. One of the possible approaches that has been proposed involves performing gestures that are recognized by a sensor and interpreted by the computer. The use of hands on a human-machine interface is justified by the fact that the hands are an important element in nonverbal communications. Due to this, in this project several possible gesture interfaces were analyzed, using the Leap Motion sensor. The project was based on the development of methods that allowed the recognition of gestures and their association to an action that the computer should perform. Through the analysis of existing studies in the area and the various methods used to allow a program to classify a data set, a gesture classification system was developed. The classification system has tested to verify its accuracy and precision. Using the knowledge obtained throughout the project, and as proof of concept, an application was developed to demonstrate the usefulness of the classification system in a real situation. This application can recognize a gesture and associate it with a keyboard key, allowing a user to write the message resulting from the gestures he makes. This project main conclusion was that the gesture classification system trained using SVM can make a good separation of the various gestures and with this classify correctly the gestures. Most of problems that arise during the recognition of a gesture are a consequence of the Leap Motion not being able to track correctly the gesture being made.application/pdfpt_PTInterfaces gestuais baseados no controlador Leap MotionBizarro, João Pedro PereiraMartins, Nuno Alexandre CidParedes, Simão Pedro Mendes Cruz ReisHostingInstitutionOrganizationalRepositório Comume-mailmailto:comum@rcaap.ptcomum@rcaap.pt2021-05-10T11:12:18Z2019-06-242018-12-132019-06-24T00:00:00ZHandlehttp://hdl.handle.net/10400.26/36452http://purl.org/coar/access_right/c_abf2open accessLeap motionHand gestureGesture interfacesGesture classificationClassification systemMotion sensor2992440 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://comum.rcaap.pt/bitstreams/167aa43e-724c-4ac2-afa1-7e35b32a1c8c/download
spellingShingle Interfaces gestuais baseados no controlador Leap Motion
Bizarro, João Pedro Pereira
Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
status SINGLETON
subject.fl_str_mv Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
title Interfaces gestuais baseados no controlador Leap Motion
title_full Interfaces gestuais baseados no controlador Leap Motion
title_fullStr Interfaces gestuais baseados no controlador Leap Motion
title_full_unstemmed Interfaces gestuais baseados no controlador Leap Motion
title_short Interfaces gestuais baseados no controlador Leap Motion
title_sort Interfaces gestuais baseados no controlador Leap Motion
topic Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
topic_facet Leap motion
Hand gesture
Gesture interfaces
Gesture classification
Classification system
Motion sensor
url http://hdl.handle.net/10400.26/36452
visible 1