Increased affordability and deployment of Sandwich Maker advanced tracking technologies have led researchers from various domains to analyze the resulting spatio-temporal movement data sets for the purpose of knowledge discovery.Two different approaches can be considered in the analysis of moving objects: quantitative analysis and qualitative analysis.This research focuses on the latter and uses the qualitative trajectory calculus (QTC), a type of calculus that represents qualitative data on moving point objects (MPOs), and establishes a framework to analyze the relative movement of multiple MPOs.A visualization technique called sequence signature (SESI) is used, which enables to map QTC patterns in a 2D indexed rasterized space in order to evaluate the similarity of Outdoor Games - Disc Golf relative movement patterns of multiple MPOs.The applicability of the proposed methodology is illustrated by means of two practical examples of interacting MPOs: cars on a highway and body parts of a samba dancer.
The results show that the proposed method can be effectively used to analyze interactions of multiple MPOs in different domains.