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Paper Abstract and Keywords
Presentation 2019-02-09 13:30
Video classification using signals and semantic level metadata for ambiguous video search
Ryunosuke Itabashi, Nobuyuki Yagi (Tokyo City Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) It is becoming possible to find the expected videos in the internet with considerable accuracy, but the developed technology does not suit to search videos, when keywords are not clear. To solve the problem, the video search method for ambiguous aim is investigated. Previous report described the results of comparative analysis between machine-learning classification with signal-level metadata and manual classification of videos chosen from NHK Creative Library, according to whether to want to watch or not at the time of relaxing. This report describes the result of classification experiment with combination of signal-level and semantic-level metadata. It is found that classification combining signal level and semantic-level metadata is more effective approach to sentimental demands.
Keyword (in Japanese) (See Japanese page) 
(in English) Video search / Ambiguous search / Video analysis / Classification / Machine learning / Image features / /  
Reference Info. ITE Tech. Rep., vol. 43, no. 4, ME2019-11, pp. 31-34, Feb. 2019.
Paper # ME2019-11 
Date of Issue 2019-02-02 (ME) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee ME  
Conference Date 2019-02-09 - 2019-02-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Kanto Gakuin University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2019-02-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Video classification using signals and semantic level metadata for ambiguous video search 
Sub Title (in English)  
Keyword(1) Video search  
Keyword(2) Ambiguous search  
Keyword(3) Video analysis  
Keyword(4) Classification  
Keyword(5) Machine learning  
Keyword(6) Image features  
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1st Author's Name Ryunosuke Itabashi  
1st Author's Affiliation Tokyo City University (Tokyo City Univ.)
2nd Author's Name Nobuyuki Yagi  
2nd Author's Affiliation Tokyo City University (Tokyo City Univ.)
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Speaker Author-1 
Date Time 2019-02-09 13:30:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # ME2019-11 
Volume (vol) vol.43 
Number (no) no.4 
Page pp.31-34 
#Pages
Date of Issue 2019-02-02 (ME) 


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