Multiview Semantic Representation for Visual Recognition
文献类型：期刊论文
| 作者 | Zhang, Chunjie1,3 ; Cheng, Jian1,2,5; Tian, Qi4
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| 刊名 | IEEE TRANSACTIONS ON CYBERNETICS
 |
| 出版日期 | 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. |
| WOS关键词 | IMAGE CLASSIFICATION ; LOW-RANK ; OBJECT CATEGORIZATION ; FUSION ; FACE |
| 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研究方向 | Automation & Control Systems ; Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000528622000023 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Science Foundation of China ; ARO ; NEC Laboratory of America ; NEC Laboratory of Blippar |
| 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 Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Res Ctr Brain Inspired Intelligence, Inst Automat, Beijing 100190, Peoples R China 4.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 5.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, 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. |
入库方式： OAI收割
来源：自动化研究所
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