We present a new compressed representation of free trajectories of moving objects. It combines a partial-sums-based structure that retrieves in constant time the position of the object at any instant, with a hierarchical minimum-bounding-boxes representation that allows determining if the object is seen in a certain rectangular area during a time period. Combined with spatial snapshots at regular intervals, the representation is shown to outperform classical ones by orders of magnitude in space, and also to outperform previous compressed representations in time performance, when using the same amount of space.
CITATION STYLE
Brisaboa, N. R., Gagie, T., Gómez-Brandón, A., Navarro, G., & Paramá, J. R. (2017). Efficient compression and indexing of trajectories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10508 LNCS, pp. 103–115). Springer Verlag. https://doi.org/10.1007/978-3-319-67428-5_10
Mendeley helps you to discover research relevant for your work.