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Temporal and video constraint databases
This dissertation proposes a general, flexible and reusable software architecture for constraint database systems. Our architecture contains several independent and coherent modules dealing with approximation, update, data representation, query evaluation, visualization and export conversion. We give a high-level description of these modules and their components, which can be modified and reused several different ways in building other systems. We implement a constraint database system based on our proposed architecture, TAQS, which is built on a spatiotemporal constraint database with linear constraints. ^ We propose an O(n) time piecewise linear approximation algorithm to approximate the temporal data into a compact constraint database representation. We also approximate the spatial data by using TIN transformation, and represent it in constraint databases. Experiments show that the piecewise linear approximation provides a significant data, reduction, and high coefficient correlation between the original data and its approximation. ^ We describe the queries based on the approximation, including simple algebraic queries, similarity queries and GIS-based queries. We evaluate the performance of the queries by using precision and recall parameters. Since the approximate database is much smaller than the original, the query evaluation becomes much faster while keeping very high precision and recall. ^ We also describe the update of the approximate temporal data and spatial data. The data is visualized by color bands display which yields static images and isometric color animation which yields a sequence of video clips for a series of spatiotemporal data. ^
Chen, Rui, "Temporal and video constraint databases" (2000). ETD collection for University of Nebraska - Lincoln. AAI9991978.