Multiview Semantic Representation for Visual Recognition

doi:10.1109/TCYB.2018.2875728

	Multiview Semantic Representation for Visual Recognition
	Zhang, Chunjie 4,5; Cheng, Jian 2,3,4; Tian, Qi 1
刊名	IEEE TRANSACTIONS ON CYBERNETICS
	2020-05-01
卷号	50 期号:5 页码:2038-2049
关键词	Image classification multiview object categorization semantic representation visual recognition
ISSN号	2168-2267
DOI	10.1109/TCYB.2018.2875728
通讯作者	Zhang, Chunjie(chunjie.zhang@ia.ac.cn)
英文摘要	Due to interclass and intraclass variations, the images of different classes are often cluttered which makes it hard for efficient classifications. The use of discriminative classification algorithms helps to alleviate this problem. However, it is still an open problem to accurately model the relationships between visual representations and human perception. To alleviate these problems, in this paper, we propose a novel multiview semantic representation (MVSR) algorithm for efficient visual recognition. First, we leverage visually based methods to get initial image representations. We then use both visual and semantic similarities to divide images into groups which are then used for semantic representations. We treat different image representation strategies, partition methods, and numbers as different views. A graph is then used to combine the discriminative power of different views. The similarities between images can be obtained by measuring the similarities of graphs. Finally, we train classifiers to predict the categories of images. We evaluate the discriminative power of the proposed MVSR method for visual recognition on several public image datasets. Experimental results show the effectiveness of the proposed method.
资助项目	National Science Foundation of China[61872362] ; National Science Foundation of China[61429201] ; ARO[W911NF-15-1-0290] ; NEC Laboratory of America ; NEC Laboratory of Blippar
WOS关键词	IMAGE CLASSIFICATION ; LOW-RANK ; OBJECT CATEGORIZATION ; FUSION ; FACE
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000528622000023
资助机构	National Science Foundation of China ; ARO ; NEC Laboratory of America ; NEC Laboratory of Blippar
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/39345]
专题	类脑芯片与系统研究
通讯作者	Zhang, Chunjie
作者单位	1.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Chunjie,Cheng, Jian,Tian, Qi. Multiview Semantic Representation for Visual Recognition[J]. IEEE TRANSACTIONS ON CYBERNETICS,2020,50(5):2038-2049.
APA	Zhang, Chunjie,Cheng, Jian,&Tian, Qi.(2020).Multiview Semantic Representation for Visual Recognition.IEEE TRANSACTIONS ON CYBERNETICS,50(5),2038-2049.
MLA	Zhang, Chunjie,et al."Multiview Semantic Representation for Visual Recognition".IEEE TRANSACTIONS ON CYBERNETICS 50.5(2020):2038-2049.