Object categorization in sub-semantic space | |
Zhang, Chunjie1![]() ![]() ![]() | |
刊名 | NEUROCOMPUTING
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2014-10-22 | |
卷号 | 142页码:248-255 |
关键词 | Object categorization Sub-semantic space Structure regularized SVM Sparse coding |
英文摘要 | Due to the semantic gap, the low-level features are unsatisfactory for object categorization. Besides, the use of semantic related image representation may not be able to cope with large inter-class variations and is not very robust to noise. To solve these problems, in this paper, we propose a novel object categorization method by using the sub-semantic space based image representation. First, exemplar classifiers are trained by separating each training image from the others and serve as the weak semantic similarity measurement. Then a graph is constructed by combining the visual similarity and weak semantic similarity of these training images. We partition this graph into visually and semantically similar sub-sets. Each sub-set of images is then used to train classifiers in order to separate this sub-set from the others. The learned sub-set classifiers are then used to Construct a sub-semantic space based representation of images. This sub-semantic space is not only more semantically meaningful than exemplar based representation but also more reliable and resistant to noise than traditional semantic space, based image representation. Finally, we make categorization of objects using this sub-semantic space with a structure regularized SVM classifier and conduct experiments on several public datasets to demonstrate the effectiveness of the proposed method. (C) 2014 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] | IMAGE CLASSIFICATION |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000340341400026 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/3363] ![]() |
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.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Beijing Univ Technol, Coll Comp Sci & Technol, Beijing 100124, Peoples R China 4.Wuhan Univ, Natl Engn Res Ctr Multimedia Software, Sch Comp, Wuhan 430072, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 6.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA |
推荐引用方式 GB/T 7714 | Zhang, Chunjie,Cheng, Jian,Liu, Jing,et al. Object categorization in sub-semantic space[J]. NEUROCOMPUTING,2014,142:248-255. |
APA | Zhang, Chunjie.,Cheng, Jian.,Liu, Jing.,Pang, Junbiao.,Liang, Chao.,...&Tian, Qi.(2014).Object categorization in sub-semantic space.NEUROCOMPUTING,142,248-255. |
MLA | Zhang, Chunjie,et al."Object categorization in sub-semantic space".NEUROCOMPUTING 142(2014):248-255. |
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