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Proceedings Paper

Flexible data organization with visualization support for a visual database system
Author(s): Lara Marie Lewis; Linda G. Shapiro; Steven L. Tanimoto
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Paper Abstract

A successful visual database system must provide facilities to manage both image data and the products extracted from them. The extracted items usually consist of textual and numeric data from which multiple visualizations can be created. Such visualizations are difficult to automate because they are domain-specific and often require data from multiple sources. In the Database Environment for Vision Research (DEVR) we address these issues. DEVR is an entity- oriented, scientific, visual database system. In DEVR, entities are stored in hierarchical, relational data structures. The schema for each entity contains a name, a set of properties, a set of parts, a set of attributed relations among the parts and a set of graphic definitions which describe how to build instance-specific visualizations. Graphic definitions are composed of one or more graphical primitives. For each primitive, the user identifies required data sources by graphically selecting various properties or parts within the schema hierarchy. As instances are created, the graphic definitions are used to automatically generate visualizations, which can later be viewed via a graphical browser. In this paper, we describe the visualization subsystem of the DEVR system, including schema construction, graphical definition, and instance browsing.

Paper Details

Date Published: 23 March 1995
PDF: 12 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205311
Show Author Affiliations
Lara Marie Lewis, Univ. of Washington (United States)
Linda G. Shapiro, Univ. of Washington (United States)
Steven L. Tanimoto, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 2420:
Storage and Retrieval for Image and Video Databases III
Wayne Niblack; Ramesh C. Jain, Editor(s)

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