Finding Stops in Error-Prone Trajectories of Moving Objects with Time-Based Clustering

M. Zimmermann, T. Kirste, and M. Spiliopoulou. Intelligent Interactive Assistance and Mobile Multimedia Computing , volume 53 of Communications in Computer and Information Science, page 275-286. Springer Berlin Heidelberg, (2009)


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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