Review and Perspective for Distance Based Trajectory Clustering

Philippe Besse; Brendan Guillouet; Jean-Michel Loubes; Royer François

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arXiv · 1508.04904

Review and Perspective for Distance Based Trajectory Clustering

Philippe Besse·Brendan Guillouet·Jean-Michel Loubes·Royer François

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Abstract

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.

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Philippe Besse, Brendan Guillouet, Jean-Michel Loubes, Royer François. 2015-08-20. Review and Perspective for Distance Based Trajectory Clustering. https://arxiv.org/abs/1508.04904

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