Finding Popular Places

Widespread availability of location aware devices (such as GPS receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects. We investigate spatio-temporal movement patterns in large tracking data sets, i.e. in large sets of polygonal paths. Specifically, we study so-called ‘popular places’, that is, regions that are visited by many entities. Given a set of polygonal paths with a total of n̄ vertices, we look at the problem of computing such popular places in two different settings. For the discrete model, where only the vertices of the polygonal paths are considered, we propose an O(n̄ log n̄) algorithm; and for the continuous model, where also the straight line segments between the vertices of a polygonal path are considered, we develop an O(n̄) algorithm. We also present lower bounds and hardness results.