MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback

被引：0
作者：
Oge Marques
Borko Furht
机构：
[1] Florida Atlantic University,Department of Computer Science and Engineering
来源：
Multimedia Tools and Applications | 2002年 / 17卷
关键词：
content-based image search and retrieval; relevance feedback; multimedia database systems; digital image processing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The field of Content-Based Visual Information Retrieval (CBVIR) has experienced tremendous growth in the recent years and many research groups are currently working on solutions to the problem of finding a desired image or video clip in a huge archive without resorting to metadata. This paper describes the ongoing development of a CBVIR system for image search and retrieval with relevance feedback capabilities. It supports browsing, query-by-example, and two different relevance feedback modes that allow users to refine their queries by indicating which images are good or bad at each iteration.
引用
收藏
页码：21 / 50
页数：29
相关论文
共 38 条
[1]  
Benitez A.(1998)Using relevance feedback in content-based image search IEEE Internet Computing 2 59-69
[2]  
Beigi M.(2000)Image retrieval by examples IEEE Transactions on Multimedia 2 164-171
[3]  
Chang S.-F.(1998)Next-generation content representation, creation and searching for new media applications in education Proceedings of the IEEE 86 884-904
[4]  
Brunelli R.(1997)Visual information retrieval from large distributed online repositories Communications of the ACM 40 63-71
[5]  
Mich O.(2000)The Bayesian image retrieval system, PicHunter: Theory, implementation, and psychophysical experiments IEEE Transactions on Image Processing 9 20-37
[6]  
Chang S.-F.(1999)An efficient low-dimensional color indexing scheme for region-based image retrieval Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing 6 3017-3020
[7]  
Eleftheriadis A.(2000)PicToSeek: Combining color and shape invariant features for image retrieval IEEE Transactions on Image Processing 9 102-119
[8]  
McClintock R.(1997)Visual information retrieval Communications of the ACM 40 71-79
[9]  
Chang S.-F.(1996)Jacob: Just a content-based query system for video database Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing 2 1216-1219
[10]  
Smith J.R.(1997)Netra: A toolbox for navigating large image databases Proceedings of the IEEE International Conference on Image Processing 1 568-571
1234