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Paper Abstract and Keywords
Presentation 2009-10-26 13:50
A note on accurate scene segmentation by video structure analysis -- An approach using new features obtained by PLSA --
Makoto Yamamoto, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) A method for accurate scene segmentation based on statistical trend analysis of audiovisual features is proposed. In the proposed method, based on the assumption that audiovisual features in the same broadcast programs include similar trends, their trends are analyzed by using Probabilistic Latent Semantic Analysis (PLSA), the method for statistical trend analysis. Then the proposed method calculates new features representing these trends. By using these new features, degradation of scene segmentation accuracy, which results from the direct use of the features obtained from the audiovisual materials, can be avoided and thereby accurate scene segmentation becomes feasible. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Scene segmentation / PLSA / Probabilistic model / Feature definition / / / /  
Reference Info. ITE Tech. Rep., vol. 33, no. 44, ME2009-177, pp. 7-10, Oct. 2009.
Paper # ME2009-177 
Date of Issue 2009-10-19 (ME) 
ISSN Print edition: ISSN 1342-6893
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Conference Information
Committee ME  
Conference Date 2009-10-26 - 2009-10-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2009-10-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A note on accurate scene segmentation by video structure analysis 
Sub Title (in English) An approach using new features obtained by PLSA 
Keyword(1) Scene segmentation  
Keyword(2) PLSA  
Keyword(3) Probabilistic model  
Keyword(4) Feature definition  
1st Author's Name Makoto Yamamoto  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Miki Haseyama  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2009-10-26 13:50:00 
Presentation Time 25 minutes 
Registration for ME 
Paper # ME2009-177 
Volume (vol) vol.33 
Number (no) no.44 
Page pp.7-10 
Date of Issue 2009-10-19 (ME) 

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