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Proceedings Paper

Implementing multilevel queries in a database environment for vision research
Author(s): Rex Jakobovits; Linda G. Shapiro; Steven L. Tanimoto
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Paper Abstract

The database environment for vision research (DEVR) is an entity-oriented scientific database system based on a hierarchical relational data model (HRS). This paper describes the design and implementation of the data definition language, the application programmer's interface, and the query mechanism of the DEVR system. DEVR provides a dynamic data definition language for modeling image and vision data, which can be integrated with existing image processing and vision applications. Schema definitions can be fully interleaved with data manipulation, without requiring recompilation. In addition, DEVR provides a powerful application programmer's interface that regulates data access and schema definition, maintains indexes, and enforces type safety and data integrity. The system supports multi-level queries based on recursive constraint trees. A set of HRS entities of a given type is filtered through a network of constraints corresponding to the parts, properties, and relations of that type. Queries can be constructed interactively with a menu-drive interface, or they can be dynamically generated within a vision application using the programmer's interface. Query objects are persistent and reusable. Users may keep libraries of query templates, which can be built incrementally, tested separately, cloned, and linked together to form more complex queries.

Paper Details

Date Published: 23 March 1995
PDF: 9 pages
Proc. SPIE 2420, Storage and Retrieval for Image and Video Databases III, (23 March 1995); doi: 10.1117/12.205321
Show Author Affiliations
Rex Jakobovits, 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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