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Proceedings Paper

Information embedding based on user's relevance feedback for image retrieval
Author(s): Catherine S. Lee; Wei-Ying Ma; HongJiang Zhang
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Paper Abstract

An image retrieval system based on an information embedding scheme is proposed. Using relevance feedback, the system gradually embeds correlations between images from a high- level semantic perspective. The system starts with low-level image features and acquires knowledge from users to correlate different images in the database. Through the selection of positive and negative examples based on a given query, the semantic relationships between images are captured and embedded into the system by splitting/merging image clusters and updating the correlation matrix. Image retrieval is then based on the resulting image clusters and the correlation matrix obtained through relevance feedback.

Paper Details

Date Published: 24 August 1999
PDF: 11 pages
Proc. SPIE 3846, Multimedia Storage and Archiving Systems IV, (24 August 1999); doi: 10.1117/12.360434
Show Author Affiliations
Catherine S. Lee, Univ. of California/Berkeley (United States)
Wei-Ying Ma, Hewlett-Packard Co. (China)
HongJiang Zhang, Hewlett-Packard Co. (China)

Published in SPIE Proceedings Vol. 3846:
Multimedia Storage and Archiving Systems IV
Sethuraman Panchanathan; Shih-Fu Chang; C.-C. Jay Kuo, Editor(s)

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