Distributed image understanding with semantic dictionary and semantic expansion | |
Li, Liang3; Yan, Chenggang Clarence2; Chen, Xing1,6; Zhang, Chunjie3; Yin, Jian4; Jiang, Baochen4; Huang, Qingming3,5 | |
刊名 | NEUROCOMPUTING |
2016-01-22 | |
卷号 | 174页码:384-392 |
关键词 | Image understanding Semantic dictionary Multi-task learning Semantic expansion Distributed systems |
ISSN号 | 0925-2312 |
DOI | 10.1016/j.neucom.2015.04.108 |
英文摘要 | Web-scale image understanding is drawing more and more attention from the computer vision and multimedia domain. To solve the key problem of visual polysemia and concept polymorphism in the image understanding, this paper proposes a semantic dictionary to describe the images on the level of semantic. The semantic dictionary characterizes the probability distribution between visual appearances and semantic concepts, and the learning procedure of semantic dictionary is formulated into a minimization optimization problem. Mixed-norm regularization is adopted to solve the above optimization for learning the concept membership distribution of visual appearance. Furthermore, to improve the generalization ability of the semantic description, we propose the semantic expansion technology, where a concept transferring matrix is learnt to quantize the implicit relevancy among the concepts. Finally, the distributed framework on the basis of the semantic dictionary is constructed to speed up the large scale image understanding. The semantic dictionary is validated in the tasks of large scale semantic image search and image annotation. (C) 2015 Elsevier B.V. All rights reserved. |
资助项目 | National Basic Research Program of China (973 Program)[2012CB316400] ; National Basic Research Program of China (973 Program)[2015CB351802] ; National Natural Science Foundation of China[61332016] ; National Natural Science Foundation of China[61025011] ; National Natural Science Foundation of China[61402431] ; National Natural Science Foundation of China[61303154] ; National Natural Science Foundation of China[11301517] ; National Natural Science Foundation of China[61472203] ; China Postdoctoral Science Foundation |
WOS研究方向 | Computer Science |
语种 | 英语 |
出版者 | ELSEVIER SCIENCE BV |
WOS记录号 | WOS:000367276700038 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/8995] |
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, Acad Math & Syst Sci, Beijing, Peoples R China 2.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China 3.Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing, Peoples R China 4.Shandong Univ, Dept Comp, Weihai, Peoples R China 5.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 6.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Liang,Yan, Chenggang Clarence,Chen, Xing,et al. Distributed image understanding with semantic dictionary and semantic expansion[J]. NEUROCOMPUTING,2016,174:384-392. |
APA | Li, Liang.,Yan, Chenggang Clarence.,Chen, Xing.,Zhang, Chunjie.,Yin, Jian.,...&Huang, Qingming.(2016).Distributed image understanding with semantic dictionary and semantic expansion.NEUROCOMPUTING,174,384-392. |
MLA | Li, Liang,et al."Distributed image understanding with semantic dictionary and semantic expansion".NEUROCOMPUTING 174(2016):384-392. |
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