Recognition and Tracking Analytics for Crowd Control
Abbad Vakil, Saransh Kacharia, Brian Hsuan-Cheng Liao, Haytham Shaban, Ibrahim Mohiuddin · viXra · 2016
We explore and apply methods of image analization in several forms in order to monitor the condition and health of a crowd. Stampedes, congestion, and traffic all occur as a result of inefficient crowd management. Our software identifies congested areas and determines solutions to avoid congestion based on live data. The data is then processed by a local device which is fed via camera. This method was tested in simulation and proved to create a more efficient and congestion-free scenario. Future plans include depth sensing for automatic calibration and suggested course of action.