Measuring Human Movement Patterns and Behaviors in Public Spaces. A method based on Thermal Cameras, Computer Vision, and Geographical Information System technologies

In order to assess human movement patterns and behaviors in public spaces we present a method using thermal cameras and Computer Vision (CV) technology, combined with the analytical virtues of Geographical Information Systems (GIS), to track people in urban streets and plazas. The method enables recording of georeferenced positions of individuals in a scene 30 times per second with a spatial accuracy about 25-50 cm. This allows for the analysis of behavior and attendance at a fine scale compared to other established methods for pedestrian behavior monitoring [1]. The use of thermal cameras has the advantage over normal cameras that they can operate independent of light, and in many situations they perform better with Computer Vision software as segmentation of moving objects is easier in thermal video. At the same time concerns for privacy issues when tracking people can be neglected since the identity of individuals cannot be revealed in thermal images. Thus the technique ensures privacy by design. Furthermore the prices on thermal cameras continue to be lowered at the same time as the resolution keeps improving [2]. This add to the practical applicability of such sensors for pedestrian behavioral studies. Our method builds on previous work by [3, 4] and extends the analysis to the GIS domain by capturing georeferenced tracks. This allows for analysis of the tracks in relation to other spatio-temporally referenced data. Environmental variables that might influence movement patterns in urban landscapes such as sunny or shaded areas, wind speed, humidity, rain, can be brought in, as well as a 3D model of the scene, or socio-economic and statistical data for the neighborhood in which the tracking is taking place.