%0 Journal Article
%T Review and Perspective for Distance Based Trajectory Clustering
%A Philippe Besse
%A Brendan Guillouet
%A Jean-Michel Loubes
%A Royer Fran£żois
%J Computer Science
%D 2015
%I arXiv
%X 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.
%U http://arxiv.org/abs/1508.04904v1