Gesture recognition of air-tapping and its application to character input in VR space

Mamoru Hirota, Masayuki Yokoyama, Ayumu Tsuboi, Masao Yanagisawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.

    Original languageEnglish
    Title of host publicationSIGGRAPH Asia 2018 Posters, SA 2018
    PublisherAssociation for Computing Machinery, Inc
    ISBN (Electronic)9781450360630
    DOIs
    Publication statusPublished - 2018 Dec 4
    EventSIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018 - Tokyo, Japan
    Duration: 2018 Dec 42018 Dec 7

    Other

    OtherSIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018
    CountryJapan
    CityTokyo
    Period18/12/418/12/7

    Fingerprint

    Electromyography
    Gesture recognition
    Muscle
    Air
    Controllers
    Experiments
    Electrodes
    Sensors

    Keywords

    • Finger Gesture Recognition,I/F
    • Interface
    • SEMG
    • VR

    ASJC Scopus subject areas

    • Computer Graphics and Computer-Aided Design
    • Human-Computer Interaction
    • Software
    • Computer Vision and Pattern Recognition

    Cite this

    Hirota, M., Yokoyama, M., Tsuboi, A., & Yanagisawa, M. (2018). Gesture recognition of air-tapping and its application to character input in VR space. In SIGGRAPH Asia 2018 Posters, SA 2018 [3283335] Association for Computing Machinery, Inc. https://doi.org/10.1145/3283289.3283335

    Gesture recognition of air-tapping and its application to character input in VR space. / Hirota, Mamoru; Yokoyama, Masayuki; Tsuboi, Ayumu; Yanagisawa, Masao.

    SIGGRAPH Asia 2018 Posters, SA 2018. Association for Computing Machinery, Inc, 2018. 3283335.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Hirota, M, Yokoyama, M, Tsuboi, A & Yanagisawa, M 2018, Gesture recognition of air-tapping and its application to character input in VR space. in SIGGRAPH Asia 2018 Posters, SA 2018., 3283335, Association for Computing Machinery, Inc, SIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018, Tokyo, Japan, 18/12/4. https://doi.org/10.1145/3283289.3283335
    Hirota M, Yokoyama M, Tsuboi A, Yanagisawa M. Gesture recognition of air-tapping and its application to character input in VR space. In SIGGRAPH Asia 2018 Posters, SA 2018. Association for Computing Machinery, Inc. 2018. 3283335 https://doi.org/10.1145/3283289.3283335
    Hirota, Mamoru ; Yokoyama, Masayuki ; Tsuboi, Ayumu ; Yanagisawa, Masao. / Gesture recognition of air-tapping and its application to character input in VR space. SIGGRAPH Asia 2018 Posters, SA 2018. Association for Computing Machinery, Inc, 2018.
    @inproceedings{67dbf6c5553b415aa1612c23196063a5,
    title = "Gesture recognition of air-tapping and its application to character input in VR space",
    abstract = "The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05{\%}. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.",
    keywords = "Finger Gesture Recognition,I/F, Interface, SEMG, VR",
    author = "Mamoru Hirota and Masayuki Yokoyama and Ayumu Tsuboi and Masao Yanagisawa",
    year = "2018",
    month = "12",
    day = "4",
    doi = "10.1145/3283289.3283335",
    language = "English",
    booktitle = "SIGGRAPH Asia 2018 Posters, SA 2018",
    publisher = "Association for Computing Machinery, Inc",

    }

    TY - GEN

    T1 - Gesture recognition of air-tapping and its application to character input in VR space

    AU - Hirota, Mamoru

    AU - Yokoyama, Masayuki

    AU - Tsuboi, Ayumu

    AU - Yanagisawa, Masao

    PY - 2018/12/4

    Y1 - 2018/12/4

    N2 - The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.

    AB - The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017].Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.

    KW - Finger Gesture Recognition,I/F

    KW - Interface

    KW - SEMG

    KW - VR

    UR - http://www.scopus.com/inward/record.url?scp=85060140100&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85060140100&partnerID=8YFLogxK

    U2 - 10.1145/3283289.3283335

    DO - 10.1145/3283289.3283335

    M3 - Conference contribution

    BT - SIGGRAPH Asia 2018 Posters, SA 2018

    PB - Association for Computing Machinery, Inc

    ER -