Presentation 2005-06-16
Video Story Segmentation based on Content-independent Low-level Features
Keiichiro HOASHI, Masaru SUGANO, Masaki NAITO, Kazunori MATSUMOTO, Fumiaki SUGAYA,
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Abstract(in English) This paper proposes a content-independent video story segmentation method based on low-level audio-video features. Conventional video story segmentation methods are dependent on content-specific features, such as anchor shot extraction results for broadcast news video, hence, are difficult to apply to video from other content domains. The proposed video story segmentation method utilizes generic audio-video features, such as color layout, motion, etc., which can be extracted from any video regardless of its content domain. Evaluation experiments conducted with TRECVID and NII-VDB data prove that the proposed method is capable of conducting highly accurate story segmentation.
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Keyword(in English) Video story segmentation / support vector machines / content-independent audio-video features
Paper # DE2005-8,PRMU2005-29
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Committee PRMU
Conference Date 2005/6/9(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Video Story Segmentation based on Content-independent Low-level Features
Sub Title (in English)
Keyword(1) Video story segmentation
Keyword(2) support vector machines
Keyword(3) content-independent audio-video features
1st Author's Name Keiichiro HOASHI
1st Author's Affiliation KDDI R&D Laboratories, Inc.()
2nd Author's Name Masaru SUGANO
2nd Author's Affiliation KDDI R&D Laboratories, Inc.
3rd Author's Name Masaki NAITO
3rd Author's Affiliation KDDI R&D Laboratories, Inc.
4th Author's Name Kazunori MATSUMOTO
4th Author's Affiliation KDDI R&D Laboratories, Inc.
5th Author's Name Fumiaki SUGAYA
5th Author's Affiliation KDDI R&D Laboratories, Inc.
Date 2005-06-16
Paper # DE2005-8,PRMU2005-29
Volume (vol) vol.105
Number (no) 118
Page pp.pp.-
#Pages 6
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