One Way Distance: For Shape Based Similarity Search of Moving Object Trajectories

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An interesting issue in moving object databases is to find similar trajectories of moving objects. Previous work on this topic focuses on movement patterns (trajectories with time dimension) of moving objects, rather than spatial shapes (trajectories without time dimension) of their trajectories. In this paper we propose a simple and effective way to compare spatial shapes of moving object trajectories. We introduce a new distance function based on “one way distance” (OWD). Algorithms for evaluating OWD in both continuous (piece wise linear) and discrete (grid representation) cases are developed. An index structure for OWD in grid representation, which guarantees no false dismissals, is also given to improve the efficiency of similarity search. Empirical studies show that OWD out-performs existent methods not only in precision, but also in efficiency. And the results of OWD in continuous case can be approximated by discrete case efficiently.

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