A Novel Spatial-Temporal Analysis Approach to Pedestrian Groups Detection

The growing availability of geo-referred data describing human behaviour, at different scales and levels of granularity, represents an opportunity for the development and application of data analysis algorithms, whose usage can range from security, to traffic, to architectural design and planning, and even marketing. Focusing on pedestrian generated trajectories, the presence of groups within an analyzed population can influence overall dynamics, from microscopic perspective, and it can provide significant indications. Several approaches for video footage analyses are available, but they generally focus on microscopic features of videos and trajectories and they are generally not suited to scale to the analysis of relatively large datasets of trajectories. The present work proposes a novel approach to spatial-temporal analysis of pedestrian trajectories aimed at detecting groups of pedestrians within large datasets and having minimal assumptions on the nature of these groups.