Real-Time Monitoring for Crowd Counting Using Video Surveillance and GIS

In public venues, crowd size is a key indicator of crowd safety and stability. Monitor the people number and crowd density levels are important scientific research topics. In this paper, we present a framework that will enable real-time crowd counting and spatial-temporal analysis for the crowd of the monitoring region. Firstly, we obtain crowd counting models for each camera by statistics regression methods using sample data. Secondly, we integrate video surveillance system and geographic information system (GIS) for capturing, managing, analyzing and displaying all forms of geographically referenced camera information, such as location, monitor area, and real-time crowd counting data, etc. And then, we combine image processing with crowd counting models to estimate people number and crowd density of monitoring areas. Finally, we implement a system for real-time crowd counting based on video surveillance system and GIS. We can acquire real-time data of people number and crowd density levels for each camera, and display them by the way of map and curves. Also, we can retrieve history data and analyze them by spatial analysis tools. The experiment shows that this system can provide early warning information and scientific basis for safety and security decision making.