Beyond visual features: A weak semantic image representation using exemplar classifiers for classification

	Beyond visual features: A weak semantic image representation using exemplar classifiers for classification
	Zhang, Chunjie1 ; Liu, Jing2 ; Tian, Qi 3; Liang, Chao 4; Huang, Qingming 1
发表期刊	NEUROCOMPUTING
	2013-11-23
期号	120 页码:318-324
文章类型	Article
摘要	Usually, the low-level representation of images is unsatisfied for image classification due to the well-known semantic gap, and further hinders its application for high-level visual applications. To deal with these problems, in this paper, we propose a simple but effective image representation for image classification, which is denoted as the responses to a set of exemplar image classifiers. Each exemplar classifier corresponding to a training image is learned using SVM algorithm to distinguish the image from others in different classes, and hence exhibits some discriminative information, which can also be regarded as a kind of weak semantic meaning. In such a one-vs-all manner, we can obtain the exemplar classifiers for all training images. We then train a linear classifier with structured sparsity constraints for each image category by taking advantages of the weak semantic image representation. Experiments on several public datasets demonstrate the effectiveness of the proposed method. (c) 2013 Elsevier B.V. All rights reserved.
关键词	Image Classification Exemplar Classifier Weak Semantic Representation Structured Sparsity
WOS标题词	Science & Technology ; Technology
关键词[WOS]	RECOGNITION ; RETRIEVAL ; GAP
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000324847100034
引用统计	被引频次：17[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/173211/3367
专题	紫东太初大模型研究中心_图像与视频分析
作者单位	1.Grad Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 4.Wuhan Univ, Sch Comp, Natl Engn Res Ctr Multimedia Software, Wuhan 430072, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Chunjie,Liu, Jing,Tian, Qi,et al. Beyond visual features: A weak semantic image representation using exemplar classifiers for classification[J]. NEUROCOMPUTING,2013(120):318-324.
APA	Zhang, Chunjie,Liu, Jing,Tian, Qi,Liang, Chao,&Huang, Qingming.(2013).Beyond visual features: A weak semantic image representation using exemplar classifiers for classification.NEUROCOMPUTING(120),318-324.
MLA	Zhang, Chunjie,et al."Beyond visual features: A weak semantic image representation using exemplar classifiers for classification".NEUROCOMPUTING .120(2013):318-324.

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