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Proceedings Paper

Psychophysical approach to modeling image semantics
Author(s): Aleksandra Mojsilovic; Bernice E. Rogowitz
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Paper Abstract

Current image retrieval systems compare images based on low- level primitives, such as color, color layout, texture and shape. However, recent psychophysical experiments show that human observers primarily use high-level semantic descriptors and categories to judge image similarity. To model. these high-level descriptors in terms of low-level primitives we use hierarchical clustering to segment the psychophysically determined image similarity space into semantically meaningful categories. We then conduct a series of psychophysical experiments to evaluate the perceptual salience of these categories. For each category we investigate the correlation with low-level pictorial features to identify semantically relevant features, their organization and distribution. Our findings suggest a new semantically based image similarity model.

Paper Details

Date Published: 8 June 2001
PDF: 8 pages
Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); doi: 10.1117/12.429518
Show Author Affiliations
Aleksandra Mojsilovic, IBM Thomas J. Watson Research Ctr. (United States)
Bernice E. Rogowitz, IBM Thomas J. Watson Research Ctr. (United States)

Published in SPIE Proceedings Vol. 4299:
Human Vision and Electronic Imaging VI
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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