Beyond visual features: A weak semantic image representation using exemplar classifiers for classification
文献类型：期刊论文
| 作者 | Zhang, Chunjie1 ; Liu, Jing2; Tian, Qi3; Liang, Chao4; Huang, Qingming1
|
| 刊名 | NEUROCOMPUTING
 |
| 出版日期 | 2013-11-23 |
| 卷号 | 120页码:318-324 |
| 关键词 | Image classification Exemplar classifier Weak semantic representation Structured sparsity |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | RECOGNITION ; RETRIEVAL ; GAP |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000324847100034 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3367]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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