Paper
8 June 2001 Psychophysical approach to modeling image semantics
Aleksandra Mojsilovic, Bernice E. Rogowitz
Author Affiliations +
Proceedings Volume 4299, Human Vision and Electronic Imaging VI; (2001) https://doi.org/10.1117/12.429518
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aleksandra Mojsilovic and Bernice E. Rogowitz "Psychophysical approach to modeling image semantics", Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); https://doi.org/10.1117/12.429518
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CITATIONS
Cited by 9 scholarly publications.
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KEYWORDS
Image retrieval

Image segmentation

Visualization

Databases

Feature extraction

Algorithm development

Data analysis

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