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

Mamoru Hirota, Masayuki Yokoyama, Ayumu Tsuboi, Masao Yanagisawa

    研究成果: Conference contribution

    抄録

    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.

    元の言語English
    ホスト出版物のタイトルSIGGRAPH Asia 2018 Posters, SA 2018
    出版者Association for Computing Machinery, Inc
    ISBN(電子版)9781450360630
    DOI
    出版物ステータスPublished - 2018 12 4
    イベントSIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018 - Tokyo, Japan
    継続期間: 2018 12 42018 12 7

    Other

    OtherSIGGRAPH Asia 2018 Posters - International Conference on Computer Graphics and Interactive Techniques, SA 2018
    Japan
    Tokyo
    期間18/12/418/12/7

    Fingerprint

    Electromyography
    Gesture recognition
    Muscle
    Air
    Controllers
    Experiments
    Electrodes
    Sensors

    ASJC Scopus subject areas

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

    これを引用

    Hirota, M., Yokoyama, M., Tsuboi, A., & Yanagisawa, M. (2018). Gesture recognition of air-tapping and its application to character input in VR space. : 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.

    研究成果: Conference contribution

    Hirota, M, Yokoyama, M, Tsuboi, A & Yanagisawa, M 2018, Gesture recognition of air-tapping and its application to character input in VR space. : 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. : 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.
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    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.",
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