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Article: Shapes based trajectory for moving objects

TitleShapes based trajectory for moving objects
Authors
KeywordsMoving Object Trajectories
One Way Distance
Similarity Search
Spatial Shape
Issue Date2005
Citation
GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 2005, p. 21-30 How to Cite?
AbstractAn interesting issue in moving objects 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. Copyright 2005 ACM.
Persistent Identifierhttp://hdl.handle.net/10722/91076
References

 

DC FieldValueLanguage
dc.contributor.authorLin, Ben_HK
dc.contributor.authorSu, Jen_HK
dc.date.accessioned2010-09-17T10:12:40Z-
dc.date.available2010-09-17T10:12:40Z-
dc.date.issued2005en_HK
dc.identifier.citationGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 2005, p. 21-30en_HK
dc.identifier.urihttp://hdl.handle.net/10722/91076-
dc.description.abstractAn interesting issue in moving objects 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. Copyright 2005 ACM.en_HK
dc.languageengen_HK
dc.relation.ispartofGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systemsen_HK
dc.subjectMoving Object Trajectoriesen_HK
dc.subjectOne Way Distanceen_HK
dc.subjectSimilarity Searchen_HK
dc.subjectSpatial Shapeen_HK
dc.titleShapes based trajectory for moving objectsen_HK
dc.typeArticleen_HK
dc.identifier.emailLin, B:blin@hku.hken_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-33644597127en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33644597127&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage21en_HK
dc.identifier.epage30en_HK

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