Presentation | 2013-06-10 Topic Models Taking into Account Burstiness of Local Features in Video Yang XIE, Koji EGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper we propose a topic model, Corr-DCMLDA, which can integrate visual words and the corresponding speech transcript words for key-frame images in each video data. Corr-DCMLDA has two distinguishing characteristics. One is the generative process that it first generates topics for visual words and then only the topics associated with the visual words are used to generate speech transcript words. The other is the assumption that the same latent topics are represented with different visual words and speech transcript words in different videos. We demonstrate through experiments on genre classification with online videos that Corr-DCMLDA works more effectively than some prior models. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Video topic modeling / Dirichlet compound multinomial models / collapsed Gibbs sampling |
Paper # | PRMU2013-20 |
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Committee | PRMU |
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Conference Date | 2013/6/3(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Topic Models Taking into Account Burstiness of Local Features in Video |
Sub Title (in English) | |
Keyword(1) | Video topic modeling |
Keyword(2) | Dirichlet compound multinomial models |
Keyword(3) | collapsed Gibbs sampling |
1st Author's Name | Yang XIE |
1st Author's Affiliation | Graduate School of Systems Informatics, Kobe University() |
2nd Author's Name | Koji EGUCHI |
2nd Author's Affiliation | Graduate School of Systems Informatics, Kobe University |
Date | 2013-06-10 |
Paper # | PRMU2013-20 |
Volume (vol) | vol.113 |
Number (no) | 75 |
Page | pp.pp.- |
#Pages | 6 |
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