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Proceedings Paper

A relevance feedback image retrieval scheme using multi-instance and pseudo-image concepts
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Paper Abstract

Content-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critical step in the content-based search. One key concept in this paper is how we find the user preferred image characteristics from the multiple positive samples provided by the user. The second key concept is that when the user does not provide a sufficient number of samples, how we generate a set of consistent "pseudo images". The notion of image feature stability is thus introduced. The third key concept is how we use negative images as pruning criterion. In realizing the preceding concepts, an image search scheme is developed using the weighted low-level image features. At the end, quantitative simulation results are used to show the effectiveness of these concepts.

Paper Details

Date Published: 17 January 2005
PDF: 12 pages
Proc. SPIE 5682, Storage and Retrieval Methods and Applications for Multimedia 2005, (17 January 2005); doi: 10.1117/12.586678
Show Author Affiliations
Feng-Cheng Chang, National Chiao Tung Univ. (Taiwan)
Hsueh-Ming Hang, National Chiao Tung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 5682:
Storage and Retrieval Methods and Applications for Multimedia 2005
Rainer W. Lienhart; Noboru Babaguchi; Edward Y. Chang, Editor(s)

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