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Contextual Exemplar Classifier-Based Image Representation for Classification
Zhang, Chunjie1,2,3; Huang, Qingming2,3,4; Tian, Qi5
2017-08-01
发表期刊IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
卷号27期号:8页码:1691-1699
文章类型Article
摘要The use of local features for image representation has become popular in recent years. Local features are often used in the bag-of-visual-words scheme. Although proven effective, this method still has two drawbacks. First, local regions from which local features are extracted are not discriminative enough for visual tasks. Hence, the combination of local features is necessary. Second, the semantic gap between visual features and human perception also hinders the performance. To address these two problems, in this paper, we propose a novel contextual exemplar classifier-based method for image representation and apply it for classification tasks. Each exemplar classifier is trained to separate one training image from the other images of different classes. We partition each image into a number of regions and use the responses of these exemplar classifiers as the image region's representation. The contextual relationship is then modeled using mixture Dirichlet distributions. A bilayer model is used to predict image classes with L-2 constraints. Experimental results on the Natural Scene, Caltech-101/256, Flower-17/102, and SUN-397 data sets show that the proposed method is able to outperform the state-of-the-art local feature-based methods for image classification.
关键词Computer Vision Image Processing Pattern Classification
WOS标题词Science & Technology ; Technology
DOI10.1109/TCSVT.2016.2527380
关键词[WOS]LOCAL FEATURES ; ADAPTATION ; RETRIEVAL ; TEXTURE ; SCENE
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61303154 ; National Basic Research Program of China (973 Program)(2012CB316400 ; Open Project of Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences ; 61332016) ; 2015CB351802)
WOS研究方向Engineering
WOS类目Engineering, Electrical & Electronic
WOS记录号WOS:000407400300007
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被引频次:9[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/15313
专题类脑智能研究中心
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
5.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA
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Zhang, Chunjie,Huang, Qingming,Tian, Qi. Contextual Exemplar Classifier-Based Image Representation for Classification[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2017,27(8):1691-1699.
APA Zhang, Chunjie,Huang, Qingming,&Tian, Qi.(2017).Contextual Exemplar Classifier-Based Image Representation for Classification.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,27(8),1691-1699.
MLA Zhang, Chunjie,et al."Contextual Exemplar Classifier-Based Image Representation for Classification".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 27.8(2017):1691-1699.
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