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Shapes based trajectory queries for moving objects

Shapes based trajectory queries for moving objects Shapes Based Trajectory Queries for Moving Objects Bin Lin and Jianwen Su Dept. of Computer Science, University of California, Santa Barbara Santa Barbara, CA, USA — linbin@cs.ucsb.edu, su@cs.ucsb.edu ABSTRACT An interesting issue in moving objects databases is to nd 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 œone 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 ef ciency of similarity search. Empirical studies show that OWD out-performs existent methods not only in precision, but also in ef ciency. And the results of OWD in continuous case can be approximated by discrete case ef ciently. Categories and Subject Descriptors H.3.3 [Database Management]: Information Search and Retrieval. General Terms Algorithms, Performance Keywords Moving object trajectories, similarity search, spatial http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Shapes based trajectory queries for moving objects

Association for Computing Machinery — Nov 4, 2005

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References (20)

Datasource
Association for Computing Machinery
Copyright
Copyright © 2005 by ACM Inc.
ISBN
1-59593-146-5
doi
10.1145/1097064.1097069
Publisher site
See Article on Publisher Site

Abstract

Shapes Based Trajectory Queries for Moving Objects Bin Lin and Jianwen Su Dept. of Computer Science, University of California, Santa Barbara Santa Barbara, CA, USA — linbin@cs.ucsb.edu, su@cs.ucsb.edu ABSTRACT An interesting issue in moving objects databases is to nd 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 œone 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 ef ciency of similarity search. Empirical studies show that OWD out-performs existent methods not only in precision, but also in ef ciency. And the results of OWD in continuous case can be approximated by discrete case ef ciently. Categories and Subject Descriptors H.3.3 [Database Management]: Information Search and Retrieval. General Terms Algorithms, Performance Keywords Moving object trajectories, similarity search, spatial

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