Relevance feedback in image retrieval: A comprehensive review

Xiang Sean Zhou, Thomas S Huang

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)536-544
Number of pages9
JournalMultimedia Systems
Issue number6
StatePublished - Apr 2003


  • Classification
  • Computer vision
  • Content-based image retrieval
  • Pattern recognition
  • Relevance feedback
  • Small sample learning

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Media Technology
  • Hardware and Architecture
  • Computer Networks and Communications


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