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Paper Abstract and Keywords
Presentation 2024-06-05 15:00
A Study on Posture Identification for Piano Learning Using Machine Learning
Yuki Michisita, Yao Bao (Tokyo City Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) The piano is a well-known instrument throughout the world, and the posture in which one plays affects one's progress on the piano. Research on piano playing posture identification has used motion capture, distance sensors, and body pressure sensors, but they require special equipment and lack versatility. In this study, we propose a method to identify the playing posture of a piano using only a camera. A posture estimation method is used, and machine learning is employed to identify the estimated postures. To confirm the effectiveness of the proposed method, posture identification was performed on the performance video. Although there were some misrecognitions, the overall agreement rate was 90% when the machine learning results were compared with the posture evaluations of experienced performers.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Posture Estimation / Image Processing / Piano / / / /  
Reference Info. ITE Tech. Rep., vol. 48, no. 16, AIT2024-150, pp. 33-36, June 2024.
Paper # AIT2024-150 
Date of Issue 2024-05-29 (AIT) 
ISSN Online edition: ISSN 2424-1970
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Conference Information
Committee IIEEJ AIT  
Conference Date 2024-06-05 - 2024-06-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo Information Design Professional University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To AIT 
Conference Code 2024-06-IIEEJ-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Posture Identification for Piano Learning Using Machine Learning 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Posture Estimation  
Keyword(3) Image Processing  
Keyword(4) Piano  
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1st Author's Name Yuki Michisita  
1st Author's Affiliation Tokyo City University (Tokyo City Univ.)
2nd Author's Name Yao Bao  
2nd Author's Affiliation Tokyo City University (Tokyo City Univ.)
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Speaker Author-1 
Date Time 2024-06-05 15:00:00 
Presentation Time 20 minutes 
Registration for AIT 
Paper # AIT2024-150 
Volume (vol) vol.48 
Number (no) no.16 
Page pp.33-36 
#Pages
Date of Issue 2024-05-29 (AIT) 


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