Trajectory clustering with mixtures of regression models
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Comparison of Distance Measures for Planar Curves
Algorithmica
Mining, indexing, and querying historical spatiotemporal data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Spatio-temporal data reduction with deterministic error bounds
The VLDB Journal — The International Journal on Very Large Data Bases
Time-focused clustering of trajectories of moving objects
Journal of Intelligent Information Systems
Computing longest duration flocks in trajectory data
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Computational Geometry: Theory and Applications
Compressing spatio-temporal trajectories
Computational Geometry: Theory and Applications
The Computational Geometry of Comparing Shapes
Efficient Algorithms
Approximating the Fréchet distance for realistic curves in near linear time
Proceedings of the twenty-sixth annual symposium on Computational geometry
Springer Handbook of Geographic Information
Springer Handbook of Geographic Information
Graphics processing unit (GPU) programming strategies and trends in GPU computing
Journal of Parallel and Distributed Computing
Of motifs and goals: mining trajectory data
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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Given a trajectory T we study the problem of reporting all subtrajectory clusters of T. To measure similarity between curves we choose the Fréchet distance. We show how the existing sequential algorithm can be modified exploiting parallel algorithms together with the GPU computational power showing substantial speed-ups. This is to the best of our knowledge not only the first GPU implementation of a subtrajectory clustering algorithm but also the first implementation using the continuous Fréchet distance, instead of the discrete Fréchet distance.