Video Analytics for Understanding Pedestrian Mobility Patterns in Public Spaces: The Case of Milan

Abstract

The main objective of this research was to characterize public spaces through a mobility study on pedestrian patterns analyzed by means of video analytics (i.e., object detection, crowd counting, pedestrian tracking), for the case study of Piazza Duomo (Milan, Italy). The analysis focused on defining different pedestrian profiles through observable behavioural parameters (e.g., density conditions, speeds, trajectories, etc.). The results of the research could support the definition of an evidence-based approach for regeneration projects of urban public spaces.