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Trajectory segmentation is the process of subdividing a trajectory into partseither by grouping points similar with respect to some measure of interest, orby minimizing a global objective function. Here we present a novel onlinealgorithm for segmentation and summary, based on point density along thetrajectory, and based on the nature of the naturally occurring structure ofintermittent bouts of locomotive and local activity. We show an application tovisualization of trajectory datasets, and discuss the use of the summary as anindex allowing efficient queries which are otherwise impossible orcomputationally expensive, over very large datasets.

Online Trajectory Segmentation and Summary With Applications to Visualization and Retrieval