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Surface-Assisted In-Air Gesture Recognition

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dc.contributor.authorKim, Minhyeok-
dc.contributor.authorLee, Donghun-
dc.contributor.authorKim, Hyosu-
dc.date.accessioned2024-03-14T07:00:24Z-
dc.date.available2024-03-14T07:00:24Z-
dc.date.issued2023-
dc.identifier.issn2162-1233-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/72847-
dc.description.abstractIn-air hand gestures can be effectively utilized to support immersive interactions in an online meeting. In this study, we propose a novel system to support in-air hand gestures by leveraging the vibrations introduced by the gestures. When a user makes hand gestures while putting her elbow on a table, vibrations are produced due to the gestures and travel through the table's surface. Based on this observation, we collect gesture-driven vibrations and use them for gesture recognition. Our evaluations with real-world users demonstrate that we can precisely recognize in-air hand gestures (e.g., an average accuracy of 96.02%) using only commercial devices, such as smartphones and smartwatches. © 2023 IEEE.-
dc.format.extent3-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE Computer Society-
dc.titleSurface-Assisted In-Air Gesture Recognition-
dc.typeArticle-
dc.identifier.doi10.1109/ICTC58733.2023.10392389-
dc.identifier.bibliographicCitationInternational Conference on ICT Convergence, v.2023 14th, pp 666 - 668-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85184570955-
dc.citation.endPage668-
dc.citation.startPage666-
dc.citation.titleInternational Conference on ICT Convergence-
dc.citation.volume2023 14th-
dc.type.docTypeConference paper-
dc.publisher.location미국-
dc.description.journalRegisteredClassscopus-
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