Relevance feedback in image retrieval: A comprehensive review

被引：0

作者：

Xiang Sean Zhou

Thomas S. Huang

机构：

[1] Siemens Corporate Research 755 College Road East,

[2] Princeton,undefined

[3] NJ 08540,undefined

[4] USA; e-mail: xzhou@scr.siemens.com ,undefined

[5] Beckman Institute for Advanced Science and Technology,undefined

[6] University of Illinois at Urbana Champaign,undefined

[7] 405 N Mathews Ave,undefined

[8] Urbana,undefined

[9] IL 61801,undefined

[10] USA; e-mail: huang@ifp.uiuc.edu ,undefined

来源：

Multimedia Systems | 2003年 / 8卷

关键词：

Key words: Relevance feedback – Content-based image retrieval – Computer vision – Classification – Pattern recognition – Small sample learning;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We analyze the nature of the relevance feedback problem in a continuous representation space in the context of content-based image retrieval. Emphasis is put on exploring the uniqueness of the problem and comparing the assumptions, implementations, and merits of various solutions in the literature. An attempt is made to compile a list of critical issues to consider when designing a relevance feedback algorithm. With a comprehensive review as the main portion, this paper also offers some novel solutions and perspectives throughout the discussion.

引用

页码：536 / 544

页数：8

共 50 条

[1] Relevance feedback in image retrieval: A comprehensive review
Zhou, XS
Huang, TS
[J]. MULTIMEDIA SYSTEMS, 2003, 8 (06) : 536 - 544
[2] Image Retrieval with relevance feedback
Fang, L
Hock, AY
[J]. 29TH APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP, PROCEEDINGS, 2000, : 85 - 91
[3] Image retrieval based on indexing and relevance feedback
Saha, Sanjoy K.
Das, Amit K.
Chanda, Bhabatosh
[J]. PATTERN RECOGNITION LETTERS, 2007, 28 (03) : 357 - 366
[4] Fuzzy relevance feedback in the semantic image retrieval
[J]. Javidi, Malihe (malihejavidi@gmail.com), 2018, Old City Publishing (30) : 4 - 6
[5] Image Retrieval Using ESNs and Relevance Feedback
Yang, Yuan-feng
Wu, Jian
Fang, Jing
Cui, Zhi-ming
[J]. 2012 11TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING & SCIENCE (DCABES), 2012, : 383 - 387
[6] Relevance feedback for semantics based image retrieval
Yoon, JH
Jayant, N
[J]. 2001 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL I, PROCEEDINGS, 2001, : 42 - 45
[7] Relevance Feedback in Image Retrieval Based on RSVM
Qi, Ya-Li
[J]. 2009 WASE INTERNATIONAL CONFERENCE ON INFORMATION ENGINEERING, ICIE 2009, VOL I, 2009, : 228 - 231
[8] Relevance feedback for cross language image retrieval
Clough, P
Sanderson, M
[J]. ADVANCES IN INFORMATION RETRIEVAL, PROCEEDINGS, 2004, 2997 : 238 - 252
[9] Kernel indexing for relevance feedback image retrieval
Peng, J
Heisterkamp, DR
[J]. 2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 1, PROCEEDINGS, 2003, : 733 - 736
[10] Fuzzy Relevance Feedback in the Semantic Image Retrieval
Javidi, Malihe
Yazdi, Hadi Sadoghi
Pourreza, H. R.
[J]. JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, 2018, 30 (4-6) : 489 - 520

← 1 2 3 4 5 →