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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Semantic Trajectory Compression
verfasst von : Falko Schmid, Kai-Florian Richter, Patrick Laube
Erschienen in: Advances in Spatial and Temporal Databases
Verlag: Springer Berlin Heidelberg
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In the light of rapidly growing repositories capturing the movement trajectories of people in spacetime, the need for trajectory compression becomes obvious. This paper argues for
semantic trajectory compression
(STC) as a means of substantially compressing the movement trajectories in an urban environment with acceptable information loss. STC exploits that human urban movement and its large–scale use (LBS, navigation) is embedded in some geographic context, typically defined by transportation networks. STC achieves its compression rate by replacing raw, highly redundant position information from, for example, GPS sensors with a semantic representation of the trajectory consisting of a sequence of
events
. The paper explains the underlying principles of STC and presents an example use case.