期刊
COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS
卷 41, 期 3, 页码 111-125出版社
ELSEVIER
DOI: 10.1016/j.comgeo.2007.10.003
关键词
moving point objects; trajectories; spatio-temporal data; computational geometry
资金
- German Science Foundation [WO 758/4-2]
- Australian Research Council
Data representing moving objects is rapidly getting more available, especially in the area of wildlife GPS tracking. It is a central belief that information is hidden in large data sets in the form of interesting patterns, where a pattern can be any configuration of some moving objects in a certain area and/or during a certain time period. One of the most common spatio-temporal patterns sought after is flocks. A flock is a large enough subset of objects moving along paths close to each other for a certain pre-defined time. We give a new definition that we argue is more realistic than the previous ones, and by the use of techniques from computational geometry we present fast algorithms to detect and report flocks. The algorithms are analysed both theoretically and experimentally. (c) 2007 Elsevier B.V. All rights reserved.
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