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Paper Abstract and Keywords
Presentation 2021-12-15 15:15
Motion Identification of Physical Exertion using Hidden Markov Model with Combined Information of Skeletal Structure and Range Data
Ryohei Yamazaki, Shigeru Akamatsu (Hosei Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) The purpose of this study is to verify the usefulness of using features that combine skeletal information and distance information for motion identification in video images. We measured the skeletal coordinates and the distance information around the palms, ankles, and head during the movements of radio gymnastics, and calculated the direction vectors of the arms and legs and the angles of the elbows, knees, and hips from the skeletal coordinates. We used the hidden Markov model for identification. As a result, the average reproduction rate of the combined feature of skeletal information and distance information increased by 5.72% compared with that of the skeletal information alone.
Keyword (in Japanese) (See Japanese page) 
(in English) Kinect / Hidden Markov model / Motion recognition / Radio gymnastics / / / /  
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Conference Information
Committee HCGSYMPO  
Conference Date 2021-12-15 - 2021-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
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Paper Information
Registration To HCGSYMPO 
Conference Code 2021-12-HCGSYMPO 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Motion Identification of Physical Exertion using Hidden Markov Model with Combined Information of Skeletal Structure and Range Data 
Sub Title (in English)  
Keyword(1) Kinect  
Keyword(2) Hidden Markov model  
Keyword(3) Motion recognition  
Keyword(4) Radio gymnastics  
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1st Author's Name Ryohei Yamazaki  
1st Author's Affiliation Hosei University (Hosei Univ.)
2nd Author's Name Shigeru Akamatsu  
2nd Author's Affiliation Hosei University (Hosei Univ.)
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Speaker Author-1 
Date Time 2021-12-15 15:15:00 
Presentation Time 90 minutes 
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