Relevance feedback in image retrieval: A comprehensive review

被引：485
作者：
Zhou, XS
Huang, TS
机构：
[1] Siemens Corp Res, Princeton, NJ 08540 USA
[2] Univ Illinois, Beckman Inst Adv Sci & Technol, Urbana, IL 61801 USA
来源：
MULTIMEDIA SYSTEMS | 2003年 / 8卷 / 06期
关键词：
relevance feedback; content-based image retrieval; computer vision; classification; pattern recognition; small sample learning;
D O I：
10.1007/s00530-002-0070-3
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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
收藏
页码：536 / 544
页数：9
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