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Paper Abstract and Keywords
Presentation 2024-02-20 14:00
A Study of Action Classification Methods from Videos Using Unsupervised Learning
Ayana Rikimaru (NIT(KOSEN), NC)
Abstract (in Japanese) (See Japanese page) 
(in English) The purpose of this study is to develop a system for automatic surveillance, and to examine whether human behavior in video can be classified into daily or extraordinary behavior. The behavior data is the coordinate data of 18 skeletal points obtained from the video images. Self-organizing maps are used to create the classification maps. Then, we examine whether the system can correctly detect the extraordinary behavior "falling down" when it is input as new data.
As a result, it was possible to detect the " falling down" behavior assuming the extraordinary behavior, but the output difference of the classification map depending on the number of times of learning was also large, and it was found necessary to set an appropriate number of times of learning.
Keyword (in Japanese) (See Japanese page) 
(in English) Action Classification / Machine Learning / Unsupervised Learning / Self-Organizing Map / / / /  
Reference Info. ITE Tech. Rep., vol. 48, no. 6, ME2024-46, pp. 148-151, Feb. 2024.
Paper # ME2024-46 
Date of Issue 2024-02-12 (MMS, ME, AIT) 
ISSN Online edition: ISSN 2424-1970
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Conference Information
Committee IEICE-ITS IEICE-IE ME AIT MMS  
Conference Date 2024-02-19 - 2024-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ME 
Conference Code 2024-02-ITS-IE-ME-AIT-MMS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study of Action Classification Methods from Videos Using Unsupervised Learning 
Sub Title (in English)  
Keyword(1) Action Classification  
Keyword(2) Machine Learning  
Keyword(3) Unsupervised Learning  
Keyword(4) Self-Organizing Map  
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1st Author's Name Ayana Rikimaru  
1st Author's Affiliation National Institute of Technology(KOSEN), Nagano College (NIT(KOSEN), NC)
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Speaker Author-1 
Date Time 2024-02-20 14:00:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # MMS2024-30, ME2024-46, AIT2024-30 
Volume (vol) vol.48 
Number (no) no.6 
Page pp.148-151 
#Pages
Date of Issue 2024-02-12 (MMS, ME, AIT) 


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