Presentation 2012-02-10
Event Detection from Video Using GMM-Supervectors and SVMs
Yusuke KAMISHIMA, Nakamasa INOUE, Koichi SHINODA, Shunsuke SATO,
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Abstract(in English) In multimedia event detection, complex target events are detected from a large set of consumer domain videos taken in unconstrained environment. We propose a multimedia event detection method using GMM supervectors and support vector machines (SVMs) with multiple features. A GMM supervector consists of the parameters of a Gaussian mixture model (GMM) which represents the distribution of local features extracted from a clip. GMMs can be regarded as an extension of the Bag-of-Words (BoW) method to a probabilistic framework, and thus, expected to be robust against the data insufficiency problem. In the experiment using the dataset of TRECVID2010 MED task, the performance of the proposed method (mean minimum NDC 0.534) was better than the conventional method based on BoW (0.565).
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Keyword(in English) Multimedia event detection / Feature extraction / GMM-Supervector / Support vector machine
Paper # PRMU2011-230,SP2011-145
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Conference Information
Committee PRMU
Conference Date 2012/2/2(1days)
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Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Event Detection from Video Using GMM-Supervectors and SVMs
Sub Title (in English)
Keyword(1) Multimedia event detection
Keyword(2) Feature extraction
Keyword(3) GMM-Supervector
Keyword(4) Support vector machine
1st Author's Name Yusuke KAMISHIMA
1st Author's Affiliation Department of Computer Science, Tokyo Institute of Technology()
2nd Author's Name Nakamasa INOUE
2nd Author's Affiliation Department of Computer Science, Tokyo Institute of Technology
3rd Author's Name Koichi SHINODA
3rd Author's Affiliation Department of Computer Science, Tokyo Institute of Technology
4th Author's Name Shunsuke SATO
4th Author's Affiliation R&D Division, Canon Inc.
Date 2012-02-10
Paper # PRMU2011-230,SP2011-145
Volume (vol) vol.111
Number (no) 430
Page pp.pp.-
#Pages 6
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