Presentation 2011-02-17
Approach to conbine Bag-of-Frames and spatio temporal features for TRECVID2010 Semantic Indexing Task.
Yasushi SHIMODA, Akitsugu NOGUCHI, Keiji YANAI,
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Abstract(in English) In this paper, we describe our approach and results for the semantics indexing task at TRECVID 2010. We focused on spatio-temporal feature and Bag-of-Prames approach. We used Multiple Kernel Learning as a fusion method to combine these various kinds of features. Since MKL can estimate weights to combine kernels, as a result of the full-category SIN task, our MKL approach yielded to get infAP=0.0478 and we reached rank 14 (among 30 teams) for the full-category SIN task and rank 12 (among 37 teams) for the light-category SIN task in TRECVID 2010.
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Keyword(in English) action recognition / spatio-temporal feature / MKL
Paper # PRMU2010-213
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Committee PRMU
Conference Date 2011/2/10(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) Approach to conbine Bag-of-Frames and spatio temporal features for TRECVID2010 Semantic Indexing Task.
Sub Title (in English)
Keyword(1) action recognition
Keyword(2) spatio-temporal feature
Keyword(3) MKL
1st Author's Name Yasushi SHIMODA
1st Author's Affiliation Department of Informatics, The University of Electro-Communication()
2nd Author's Name Akitsugu NOGUCHI
2nd Author's Affiliation Department of Informatics, The University of Electro-Communication
3rd Author's Name Keiji YANAI
3rd Author's Affiliation Department of Informatics, The University of Electro-Communication
Date 2011-02-17
Paper # PRMU2010-213
Volume (vol) vol.110
Number (no) 414
Page pp.pp.-
#Pages 6
Date of Issue