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Dual structure constrained multimodal feature coding for social event detection from flickr data
Yang Z.1; Li Q.3; Lu Z.3; Ma Y.3; Gong Z.2; Liu W.1
2017-03-01
Source PublicationACM Transactions on Internet Technology
ISSN15576051 15335399
Volume17Issue:2
AbstractIn this work, a three-stage social event detection (SED) framework is proposed to discover events from Flickr-like data. First, multiple bipartite graphs are constructed for the heterogeneous feature modalities to achieve fused features. Furthermore, considering the geometrical structures of dictionary and data, a dual structure constrained multimodal feature coding model is designed to learn discriminative feature codes by incorporating corresponding regularization terms into the objective. Finally, clustering models utilizing density or label knowledge and data recovery residual models are devised to discover real-world events. The proposed SED approach achieves the highest performance on the MediaEval 2014 SED dataset.
KeywordEvent detection Feature coding Multimedia content analysis Multimodal fusion Social multimedia analytics
DOI10.1145/3015463
URLView the original
Language英語
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Guangdong University of Technology
2.Universidade de Macau
3.City University of Hong Kong
Recommended Citation
GB/T 7714
Yang Z.,Li Q.,Lu Z.,et al. Dual structure constrained multimodal feature coding for social event detection from flickr data[J]. ACM Transactions on Internet Technology,2017,17(2).
APA Yang Z.,Li Q.,Lu Z.,Ma Y.,Gong Z.,&Liu W..(2017).Dual structure constrained multimodal feature coding for social event detection from flickr data.ACM Transactions on Internet Technology,17(2).
MLA Yang Z.,et al."Dual structure constrained multimodal feature coding for social event detection from flickr data".ACM Transactions on Internet Technology 17.2(2017).
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