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

Feng-Cheng Chang; Hsueh-Ming Hang

doi:10.1117/12.586678

17 January 2005 A relevance feedback image retrieval scheme using multi-instance and pseudo-image concepts

Feng-Cheng Chang, Hsueh-Ming Hang

Proceedings Volume 5682, Storage and Retrieval Methods and Applications for Multimedia 2005; (2005) https://doi.org/10.1117/12.586678
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

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.

Citation Download Citation

Feng-Cheng Chang and Hsueh-Ming Hang "A relevance feedback image retrieval scheme using multi-instance and pseudo-image concepts", Proc. SPIE 5682, Storage and Retrieval Methods and Applications for Multimedia 2005, (17 January 2005); https://doi.org/10.1117/12.586678

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