Efficient Compression and Indexing of Trajectories

TL;DR

This paper introduces a novel compressed data structure for moving object trajectories that enables fast position retrieval and spatial queries, significantly reducing space and improving query performance over traditional methods.

Contribution

It proposes a combined partial-sums and hierarchical bounding box structure for efficient trajectory compression and querying, outperforming classical and previous compressed approaches.

Findings

Outperforms classical representations in space efficiency

Achieves faster query times with the same space budget

Significantly reduces storage requirements for trajectory data

Abstract

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.