Clustering Moving Object Trajectories: Integration in CROSS-CPP Analytic Toolbox

Mobile devices equipped with sensors are generating an amount of geo-spatial related data that, properly analyzed can be used for future applications. In particular, being able to establish similar trajectories is crucial to analyze events on common points in the trajectories. CROSS-CPP is a European project whose main aim is to provide tools to store data in a data market and to have a toolbox to analyze the data. As part of these analytic tools, a set of functionalities has been developed to cluster trajectories. Based on previous work on clustering algorithms we present in this paper a Quickbundels algorithm adaptation to trajectory clustering . Experiments using different distance measures show that Quickbundles outperforms spectral clustering, with the WS84 geodesic distance being the one that provides the best results.

Automated summary

Mobile devices with sensors generate geo-spatial data for future applications, with trajectory clustering being crucial for analyzing common point events. The CROSS-CPP project aims to provide tools for data storage and analysis, with an adapted Quickbundles algorithm showing superior performance in trajectory clustering experiments using various distance measures.