Review and Perspective for Distance Based Trajectory Clustering

20 Aug 2015  ·  Philippe Besse, Brendan Guillouet, Jean-Michel Loubes, Royer François ·

In this paper we tackle the issue of clustering trajectories of geolocalized observations. Using clustering technics based on the choice of a distance between the observations, we first provide a comprehensive review of the different distances used in the literature to compare trajectories... Then based on the limitations of these methods, we introduce a new distance : Symmetrized Segment-Path Distance (SSPD). We finally compare this new distance to the others according to their corresponding clustering results obtained using both hierarchical clustering and affinity propagation methods. read more

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