Speeding up relevance feedback in image retrieval with triangle-inequality based algorithms

Ziyou Xiong, Xiang Zhou, William M. Pottenger, Thomas S. Huang

Research output: Contribution to journalConference articlepeer-review


A content-based image retrieval (CBIR) system has been constructed to integrate relevance feedback with triangle-inequality based algorithms. The system offers typically 20 to 30 times faster retrieving speed with minimum sacrifice of retrieval performance on Corel database consisting of more than 17,000 images. The theoretic framework is built by using triangle-inequality based algorithms at sub-feature level and using relevance feedback techniques at feature level. Results show retrieval performance is clearly improved over the approach with only triangle-inequality based algorithms. A new high level weight updating method for the hierarchical distance model for relevance feedback is proposed.

Original languageEnglish (US)
Pages (from-to)IV/3373-IV/3376
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 2002
Externally publishedYes
Event2002 IEEE International Conference on Acoustic, Speech, and Signal Processing - Orlando, FL, United States
Duration: May 13 2002May 17 2002

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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