Designing Huge Repositories of Moving Vehicles Trajectories for Efficient Extraction of Semantic Data

The rapid development of digital cameras equipped with video analytics software is providing the availability of large amount of traffic data describing the trajectories traced by each vehicle and person within a scene. These data offer enormous potential when coupled with a querying system able to extract synthetic but meaningful information as those obtained by spatiotemporal queries; the latter allow, for instance, to select all those trajectories passing through some parts of the scene, even in given sequences, and adding restrictions on the properties of the objects (the category of the vehicles, their color and size, and so on). In this paper we propose a novel system for efficiently storing and querying large amounts of 3D data (trajectories over time), specifically designed for making possible the formulation of a wide variety of spatio-temporal 3D queries. The method is based on a novel 3D data schema which is reconducted to a set of 2D schemata, being the latter the only ones available in currently ready-to-use database environments. An implementation of the system over PostGIS is presented in this paper, together with a performance assessment on a huge trajectory database. The obtained results confirm the effectiveness of the proposed approach and its applicability to real applications.