Surpassing the information theoretic bound with fusion trees
Journal of Computer and System Sciences - Special issue: papers from the 22nd ACM symposium on the theory of computing, May 14–16, 1990
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Algorithmic issues in modeling motion
ACM Computing Surveys (CSUR)
On-line data reduction and the quality of history in moving objects databases
MobiDE '06 Proceedings of the 5th ACM international workshop on Data engineering for wireless and mobile access
Sampling Trajectory Streams with Spatiotemporal Criteria
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Preserving order in a forest in less than logarithmic time
SFCS '75 Proceedings of the 16th Annual Symposium on Foundations of Computer Science
Understanding mobility based on GPS data
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
Algorithms for compressing GPS trajectory data: an empirical evaluation
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
TrajMetrix: a trajectory compression benchmarking framework
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Compact representation of GPS trajectories over vectorial road networks
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
EHSTC: an enhanced method for semantic trajectory compression
Proceedings of the 4th ACM SIGSPATIAL International Workshop on GeoStreaming
Direction-preserving trajectory simplification
Proceedings of the VLDB Endowment
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GPS-equipped mobile devices such as smart phones and in-car navigation units are collecting enormous amounts spatial and temporal information that traces a moving object's path. The popularity of these devices has led to an exponential increase in the amount of GPS trajectory data generated. The size of this data makes it difficult to transmit it over a mobile network and to analyze it to extract useful patterns. Numerous compression algorithms have been proposed to reduce the size of trajectory data sets; however these methods often lose important information essential to location-based applications such as object's position, time and speed. This paper describes the Spatial QUalIty Simplification Heuristic (SQUISH) method that demonstrates improved performance when compressing up to roughly 10% of the original data size, and preserves speed information at a much higher accuracy under aggressive compression. Performance is evaluated by comparison with three competing trajectory compression algorithms: Uniform Sampling, Douglas-Peucker and Dead Reckoning.