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Human Action Recognition Using Acceleration Information Based On Hidden Markov Model

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/39816

Title: Human Action Recognition Using Acceleration Information Based On Hidden Markov Model
Authors: Takeuchi, Shin'ichi Browse this author
Tamura, Satoshi Browse this author
Hayamizu, Satoru Browse this author
Issue Date: 4-Oct-2009
Publisher: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee
Journal Title: Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
Start Page: 829
End Page: 832
Abstract: 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.
Description: 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).
Conference Name: APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference
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
Conference Place: Sapporo
Type: proceedings
URI: http://hdl.handle.net/2115/39816
Appears in Collections:北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 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 (2009 APSIPA Annual Summit and Conference)

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