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Proceedings Paper

Adaptive visual querying of image databases
Author(s): Eric Y. Tao; Jack Sklansky
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Paper Abstract

We describe techniques for adaptive nonverbal visual querying of large databases of images. The technique facilitates (a) visual mapping, a technique visualizing the relationships among the images, revealed by plotting each image as a point in a multidimensional `feature space,' and (b) interactive selection of features to maximize the correspondence between the clusters in feature space and the user's understanding of the relationships among the stored images. We refer to these techniques of querying as Adaptive visual querying. Adaptive visual querying will facilitate browsing and searching image databases from examples of images and from computer-aided sketches.

Paper Details

Date Published: 8 March 1996
PDF: 7 pages
Proc. SPIE 2656, Visual Data Exploration and Analysis III, (8 March 1996); doi: 10.1117/12.234658
Show Author Affiliations
Eric Y. Tao, Univ. of California/Irvine (United States)
Jack Sklansky, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 2656:
Visual Data Exploration and Analysis III
Georges G. Grinstein; Robert F. Erbacher, Editor(s)

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