Contextual Exemplar Classifier-Based Image Representation for Classification

doi:10.1109/TCSVT.2016.2527380

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Contextual Exemplar Classifier-Based Image Representation for Classification
	Zhang, Chunjie 2,3,4; Huang, Qingming 1,3,4; Tian, Qi 5
刊名	IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
	2017-08-01
卷号	27 期号:8 页码:1691-1699
关键词	Computer vision image processing pattern classification
ISSN号	1051-8215
DOI	10.1109/TCSVT.2016.2527380
英文摘要	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.
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	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000407400300007
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/6598]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Chunjie
作者单位	1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, 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,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.