Abstract
An important problem in the study of moving objects is the identification of stops. This problem becomes more difficult due to error-prone recording devices. We propose a method that discovers stops in a trajectory that contains artifacts, namely movements that did not actually take place but correspond to recording errors. Our method is an interactive density-based clustering algorithm, for which we define density on the basis of both the spatial and the temporal properties of a trajectory. The interactive setting allows the user to tune the algorithm and to study the stability of the anticipated stops.
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Zimmermann, M., Kirste, T., Spiliopoulou, M. (2009). Finding Stops in Error-Prone Trajectories of Moving Objects with Time-Based Clustering. In: Tavangarian, D., Kirste, T., Timmermann, D., Lucke, U., Versick, D. (eds) Intelligent Interactive Assistance and Mobile Multimedia Computing. IMC 2009. Communications in Computer and Information Science, vol 53. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10263-9_24
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DOI: https://doi.org/10.1007/978-3-642-10263-9_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10262-2
Online ISBN: 978-3-642-10263-9
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