Paper
30 August 2002 Self-adaptive semantic schema mechanism for multimedia databases
Jun Yang, Qing Li, Yueting Zhuang
Author Affiliations +
Abstract
In the context of multimedia retrieval, the goal of accuracy is to a certain extent contradictory with that of efficiency. The former relies on exploiting sophisticated features, whereas the latter favors using simple features with reduced dimensionality. As an endeavor to strike the balance between these two goals, this paper presents a self-adaptive semantic schema mechanism (SSM) for multimedia databases. The SSM is implemented based on an object-oriented data model, with classes being organized into a semantic hierarchy. As its most distinguishable feature, when the conditions of certain ECA-rules are satisfied, SSM supports adaptive evolution of a schema in the form of expansion with new classes and/or compaction by removing inefficient ones. This self-adaptive evolution strategy allows a schema to optimize for the requirements of each specific application, thereby achieving a dynamic, application-specific balance between accuracy and efficiency. A prototype system for multimedia retrieval, 2M2Net, has been built based on this mechanism and validated for its feasibility.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Yang, Qing Li, and Yueting Zhuang "Self-adaptive semantic schema mechanism for multimedia databases", Proc. SPIE 4925, Electronic Imaging and Multimedia Technology III, (30 August 2002); https://doi.org/10.1117/12.481571
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Cited by 1 scholarly publication.
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KEYWORDS
Databases

Multimedia

Data modeling

Prototyping

Computer vision technology

Feature extraction

Machine vision

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