様々な人体動作に対するパイスタティック散乱特性の大規模データセットの合成

• Item type: SIG Technical Reports(1)
• 公開日: 2019-02-25
• タイトル: 様々な人体動作に対するパイスタティック散乱特性の大規模データセットの合成
• タイトル / 言語: en
• タイトル: Towards motion recognition by ubiquitous RF sensing: a large synthetic dataset of bistatic scattering from human body in motion
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: 東京工業大学工学部
• 著者所属: 東京工業大学工学部
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Tokyo Institute of Technology
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Engineering, Tokyo Institute of Technology
• 著者名: 龐, 海涛; 高田, 潤一
• 著者名(英): Haitao, Pang; Jun-ichi, Takada
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This paper discusses using electromagnetic (EM) signals of wireless communication for human motion recognition (HMR) via radio frequency (RF) sensing. Modern high data-rate RF communication systems have inherent sensing capabilities for moving objects. Contact-less, device-less, camera-less HMR by ordinary radio signals is very advantageous compared with traditional method by computer vision or wearables. However, the physical phenomena of RF scattering from biological bodies are complicated and dependent on many factors such as shape, material properties, polarization, geometry, etc. To demonstrate this, we focus on the characteristics of time variant scattering from a human body performing various kinds of motions, in a data-centric manner. Using inputs of measured motion data, generative human models in various postures, and a numerical EM simulator based on a high frequency asymptotic method of physical optics (PO), large datasets can be generated. This can be used for better and more comprehensive understanding of the RF interaction with human body, and for development and comparison of future robust recognition RF algorithms and joint communication and radar (RAdio Detection And Ranging) devices.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This paper discusses using electromagnetic (EM) signals of wireless communication for human motion recognition (HMR) via radio frequency (RF) sensing. Modern high data-rate RF communication systems have inherent sensing capabilities for moving objects. Contact-less, device-less, camera-less HMR by ordinary radio signals is very advantageous compared with traditional method by computer vision or wearables. However, the physical phenomena of RF scattering from biological bodies are complicated and dependent on many factors such as shape, material properties, polarization, geometry, etc. To demonstrate this, we focus on the characteristics of time variant scattering from a human body performing various kinds of motions, in a data-centric manner. Using inputs of measured motion data, generative human models in various postures, and a numerical EM simulator based on a high frequency asymptotic method of physical optics (PO), large datasets can be generated. This can be used for better and more comprehensive understanding of the RF interaction with human body, and for development and comparison of future robust recognition RF algorithms and joint communication and radar (RAdio Detection And Ranging) devices.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11851388
• 書誌情報: 研究報告モバイルコンピューティングとパーベイシブシステム（MBL）; 巻 2019-MBL-90, 号 30, p. 1-5, 発行日 2019-02-25
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8817
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会