Boosted random contextual semantic space based representation for visual recognition

doi:10.1016/j.ins.2016.06.029

	Boosted random contextual semantic space based representation for visual recognition
	Zhang, Chunjie 1; Xue, Zhe 1; Zhu, Xiaobin 2; Wang, Huanian 3; Huang, Qingming 1,4; Tian, Qi 5
	2016-11-10
发表期刊	INFORMATION SCIENCES
ISSN	0020-0255
卷号	369 页码:160-170
摘要	Visual information has been widely used for image representation. Although proven very effective, the visual representation lacks explicit semantics. However, how to generate a proper semantic space for image representation is still an open problem that needs to be solved. To jointly model the visual and semantic representations of images, we propose a boosted random contextual semantic space based image representation method. Images are initially represented using local feature's distribution histograms. The semantic space is generated by randomly selecting training images. Images are then mapped into the semantic space accordingly. Semantic context is explored to model the correlations of different semantics which is then used for classification. The classification results are used to re-weight training images in a boosted way. The re-weighted images are used to construct new semantic space for classification. In this way, we are able to jointly consider the visual and semantic information of images. Image classification experiments on several public datasets show the effectiveness of the proposed method. (C) 2016 Elsevier Inc. All rights reserved.
关键词	Pattern recognition Image processing Visual representation
DOI	10.1016/j.ins.2016.06.029
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61303154] ; National Natural Science Foundation of China[61332016] ; National Basic Research Program of China (973 Program)[2012CB316400] ; National Basic Research Program of China (973 Program)[2015CB351802] ; Open Project of Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000383292500011
出版者	ELSEVIER SCIENCE INC
引用统计	被引频次：20[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8147
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhu, Xiaobin
作者单位	1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 2.Beijing Technol & Business Univ, Beijing, Peoples R China 3.Cent Univ Finance & Econ, Beijing, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
推荐引用方式 GB/T 7714	Zhang, Chunjie,Xue, Zhe,Zhu, Xiaobin,et al. Boosted random contextual semantic space based representation for visual recognition[J]. INFORMATION SCIENCES,2016,369:160-170.
APA	Zhang, Chunjie,Xue, Zhe,Zhu, Xiaobin,Wang, Huanian,Huang, Qingming,&Tian, Qi.(2016).Boosted random contextual semantic space based representation for visual recognition.INFORMATION SCIENCES,369,160-170.
MLA	Zhang, Chunjie,et al."Boosted random contextual semantic space based representation for visual recognition".INFORMATION SCIENCES 369(2016):160-170.