Robust Interpolation of Arbitrary-Dimensional Moving Regions in Databases

Moving Objects Databases are designed to store, process and efficiently search for database objects with attributes that can change over time. Examples are moving points, that change position over time, or, as a more complex data type, moving regions that can also change shape. For moving regions to be practically usable, methods for creating those objects have to be provided. The prevailing method for 2-dimensional moving regions is to create an interpolation of two static regions. Since this is a non-trivial task, this is referred to as the "Region Interpolation Problem", which still can not be considered as solved, since several unsolved questions remain. This work strives to give an overview on the Region Interpolation Problem, discuss an extension to 3d and higher dimensions and to present and discuss solutions to address some of the remaining obstacles.

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Published
2024-10-22
DOI
https://doi.org/10.1145/3681769.3698579
Primary Topic
Data Management and Algorithms
Type
article
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Robust Interpolation of Arbitrary-Dimensional Moving Regions in Databases

Florian Heinz
Data Management and Algorithms
article

Robust Interpolation of Arbitrary-Dimensional Moving Regions in Databases

Florian Heinz
article en

Abstract

Moving Objects Databases are designed to store, process and efficiently search for database objects with attributes that can change over time. Examples are moving points, that change position over time, or, as a more complex data type, moving regions that can also change shape. For moving regions to be practically usable, methods for creating those objects have to be provided. The prevailing method for 2-dimensional moving regions is to create an interpolation of two static regions. Since this is a non-trivial task, this is referred to as the "Region Interpolation Problem", which still can not be considered as solved, since several unsolved questions remain. This work strives to give an overview on the Region Interpolation Problem, discuss an extension to 3d and higher dimensions and to present and discuss solutions to address some of the remaining obstacles.

OTH Regensburg (DE)
Openalex Percentile: Top 80%
Data Management and Algorithms
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