Type
Conference PaperAuthors
Ismail, Anas
Vigneron, Antoine E.

KAUST Department
Computer Science ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Visual Computing Center (VCC)
Date
2016-08-08Online Publication Date
2016-08-08Print Publication Date
2015Permanent link to this record
http://hdl.handle.net/10754/622504
Metadata
Show full item recordAbstract
We present a new algorithm for measuring the similarity between trajectories, and in particular between GPS traces. We call this new similarity measure the Merge Distance (MD). Our approach is robust against subsampling and supersampling. We perform experiments to compare this new similarity measure with the two main approaches that have been used so far: Dynamic Time Warping (DTW) and the Euclidean distance. © 2015 ACM.Citation
Ismail A, Vigneron A (2015) A New Trajectory Similarity Measure for GPS Data. Proceedings of the 6th ACM SIGSPATIAL International Workshop on GeoStreaming - IWGS’15. Available: http://dx.doi.org/10.1145/2833165.2833173.Sponsors
Anas Ismail was supported by KAUST base fundingConference/Event name
6th ACM SIGSPATIAL International Workshop on GeoStreaming, IWGS 2015Additional Links
http://dl.acm.org/citation.cfm?doid=2833165.2833173ae974a485f413a2113503eed53cd6c53
10.1145/2833165.2833173