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

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Abstract

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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Acknowledgements

Supported in part by NSF grants IIS-0101134 and IIS-0415195.

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Authors and Affiliations

  1. Department of Computer Science, University of California, Santa Barbara, USA

    Bin Lin & Jianwen Su

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  1. Bin Lin
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  2. Jianwen Su
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Correspondence to Bin Lin.

Additional information

The preliminary version of this paper was published in ACMGIS 2005 (B. Lin and J. Su. “Shapes based trajectory queries for moving objects,” pp. 21–30).

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Lin, B., Su, J. One Way Distance: For Shape Based Similarity Search of Moving Object Trajectories. Geoinformatica 12, 117–142 (2008). https://doi.org/10.1007/s10707-007-0027-y

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  • DOI: https://doi.org/10.1007/s10707-007-0027-y

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