Efficient Compression and Indexing of Trajectories

Nieves Brisaboa, Travis Gagie, Adrián Gómez-Brandón, Gonzalo Navarro, and Jose Parama

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.