Partition and Density-based Clustering for Moving Objects trajectories

摘要

Since the trajectory of a moving object contains a lot of information, it is an interesting task to analyze trajectories for several application areas. Clustering common sub-trajectories is one of them. We propose a method T-CLUS to partition a trajectory into line segments, and then generate the augmented cluster-ordering of the line segments; finally identify cluster structure by means of reachability plot. Experimental results demonstrate that T-CLUS is scalable and accurate to discover common sub-trajectories from a trajectory database.