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Dynamics-aware similarity of moving objects trajectories
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Source Geographic Information Systems archive
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems table of contents
Seattle, Washington
SESSION: Trajectories table of contents
Article No. 11  
Year of Publication: 2007
ISBN:978-1-59593-914-2
Authors
Goce Trajcevski  Northwestern University
Hui Ding  Northwestern University
Peter Scheuermann  Northwestern University
Roberto Tamassia  Brown University
Dennis Vaccaro  Northrop Grumman Corp.
Sponsors
: Oak Ridge National Laboratory
: Google
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
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ABSTRACT

This work addresses the problem of obtaining the degree of similarity between trajectories of moving objects. Typically, a Moving Objects Database (MOD) contains sequences of (location, time) points describing the motion of individual objects, however, they also implicitly storethe velocity -- an important attribute describing the dynamics the motion. Our main goal is to extend the MOD capability with reasoning about how similar are the trajectories of objects, possibly moving along geographically different routes. We use a distance function which balances the lack of temporal-awareness of the Hausdorff distance with the generality (and complexity of calculation) of the Fréchet distance. Based on the observation that in practice the individual segments of trajectories are assumed to have constant speed, we provide efficient algorithms for: (1) optimal matching between trajectories; and (2) approximate matching between trajectories, both under translations and rotations, where the approximate algorithm guarantees a bounded error with respect to the optimal one.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Goce Trajcevski: colleagues
Hui Ding: colleagues
Peter Scheuermann: colleagues
Roberto Tamassia: colleagues
Dennis Vaccaro: colleagues