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北海道大学サステナビリティ・ウィーク2009  >
2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議  >

Human Action Recognition Using Acceleration Information Based On Hidden Markov Model

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タイトル: Human Action Recognition Using Acceleration Information Based On Hidden Markov Model
著者: Takeuchi, Shin'ichi 著作を一覧する
Tamura, Satoshi 著作を一覧する
Hayamizu, Satoru 著作を一覧する
発行日: 2009年10月 4日
出版者: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee
誌名: Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
開始ページ: 829
終了ページ: 832
抄録: This paper investigates the best feature parameter for human action recognition by using Hidden Markov Model (HMM) with triaxial acceleration sensor information. Our target is to recognize six types of basic actions (walk, stay, sit down, stand up, lie down, get up) in the room of daily life. First, as parameters in time domain, acceleration information in three axes and their derivatives are used as the baseline method. Secondly, Mel-Frequency Cepstral Coefficients are used as feature parameters in frequency domain. As the recognition result, the best recognition rate was obtained when MFCC and its Δ elements of the axis that contained most of gravitational acceleration information.
記述: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Poster session: Image, Video, and Multimedia Signal Processing 3 (7 October 2009).
資料タイプ: proceedings
URI: http://hdl.handle.net/2115/39816
出現コレクション:2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)

 

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