中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
LSH-based semantic dictionary learning for large scale image understanding

文献类型：期刊论文

作者Li, Liang1; Yan, Chenggang Clarence2; Ji, Wen3; Chen, Bo-Wei4; Jiang, Shuqiang3; Huang, Qingming1,3
刊名JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
出版日期2015-08-01
卷号31页码:231-236
关键词Locality sensitive hashing Online dictionary learning Spatial pyramid matching Image understanding
ISSN号1047-3203
DOI10.1016/j.jvcir.2015.06.008
英文摘要Large scale image understanding is a challenging but significant task to comprehend image contents on the internet. The de-facto standard methods based on machine learning or computer vision still suffer from a phenomenon of visual polysemia and concept polymorphism (VPCP). To resolve the VPCP, semantic dictionary has been proposed to characterize the membership distribution between visual appearances and semantic concepts. In this paper, we propose an online semantic dictionary learning algorithm on the base of both locality sensitive hashing (LSH) and stochastic approximations, which can scale up to large scale datasets with millions of training samples and speedup the efficiency of follow-up processing. With the help of the LSH-based semantic dictionary, we develop an extension of the spatial pyramid matching (SPM) kernel method by generalizing the dictionary as a basic semantic description. The efficiency of our approach is validated in the experiments of web-scale semantic image search and image classification on the ImageNet dataset and Caltech-256 dataset. (C) 2015 Published by Elsevier Inc.
资助项目National Basic Research Program of China (973 Program)[2012CB316400] ; National Basic Research Program of China (973 Program)[2015CB351802] ; National 275 Natural Science Foundation of China[61332016] ; National 275 Natural Science Foundation of China[61025011] ; National 275 Natural Science Foundation of China[61402431] ; National 275 Natural Science Foundation of China[61472203] ; China Postdoctoral Science Foundation
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000359181600021
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
源URL[http://119.78.100.204/handle/2XEOYT63/9483]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Yan, Chenggang Clarence
作者单位1.Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing, Peoples R China
2.Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
4.Princeton Univ, Dept Elect Engn, Princeton, NJ 08544 USA
推荐引用方式
GB/T 7714		 Li, Liang,Yan, Chenggang Clarence,Ji, Wen,et al. LSH-based semantic dictionary learning for large scale image understanding[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2015,31:231-236.
APA Li, Liang,Yan, Chenggang Clarence,Ji, Wen,Chen, Bo-Wei,Jiang, Shuqiang,&Huang, Qingming.(2015).LSH-based semantic dictionary learning for large scale image understanding.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,31,231-236.
MLA Li, Liang,et al."LSH-based semantic dictionary learning for large scale image understanding".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 31(2015):231-236.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。