Similar sub-trajectory retrieval for moving objects in spatio-temporal databases

Moving objects' trajectories play an important role in doing efficient retrieval in spatial-temporal databases. In this paper, we propose a spatiotemporal representation scheme for modeling the trajectory of moving objects. Our spatio-temporal representation scheme effectively describes not only the single trajectory of a moving object but also the multiple trajectories of two or more moving objects. For measuring similarity between two trajectories, we propose a new k-warping distance algorithm which enhances the existing time warping distance algorithm by permitting up to k replications for an arbitrary motion of a query trajectory. Our k-warping distance algorithm provides an approximate matching between two trajectories as well as an exact matching between them. Based on our k-warping distance algorithm, we also present a similarity measure scheme for both the single trajectory and the multiple trajectories in spatio-temporal databases. Finally, we show from our experiment that our similarity measure scheme based on the k-warping distance outperforms Li's one (no-warping) and Shan's one (infinite-warping) in terms of precision and recall measures.