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Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning

文献类型：期刊论文

作者Li, Bing1; Yuan, Chunfeng1; Xiong, Weihua1; Hu, Weiming2; Peng, Houwen1; Ding, Xinmiao1; Maybank, Steve3
刊名IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
出版日期2017-12-01
卷号39期号:12页码:2554-2560
关键词Multi-instance Learning Multi-view Sparse Representation Dictionary Learning
DOI10.1109/TPAMI.2017.2669303
文献子类Article
英文摘要In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm ((MIL)-I-2) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse epsilon-graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the M2IL. Experiments and analyses in many practical applications prove the effectiveness of the M2IL.
WOS关键词IMAGE RETRIEVAL ; RECOGNITION ; CLASSIFICATION ; ALGORITHM
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000414395400017
资助机构Natural Science Foundation of China(61370038 ; 973 basic research program of China(2014CB349303) ; CAS(XDB02070003) ; Youth Innovation Promotion Association, CAS ; U1636218 ; 61472421 ; 61571045)
源URL[http://ir.ia.ac.cn/handle/173211/19566]  
专题自动化研究所_模式识别国家重点实验室_视频内容安全团队
作者单位1.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat,Natl Lab Pattern Recognit, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100049, Peoples R China
3.Birkbeck Coll, Dept Comp Sci & Informat Syst, London WC1E 7HX, England
推荐引用方式
GB/T 7714		 Li, Bing,Yuan, Chunfeng,Xiong, Weihua,et al. Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2017,39(12):2554-2560.
APA Li, Bing.,Yuan, Chunfeng.,Xiong, Weihua.,Hu, Weiming.,Peng, Houwen.,...&Maybank, Steve.(2017).Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,39(12),2554-2560.
MLA Li, Bing,et al."Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 39.12(2017):2554-2560.

入库方式： OAI收割

来源：自动化研究所

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