Crowd navigation monitoring during emergencies

The paper considers the task of crowd navigation monitoring, which might be performed using various sensors and technologies, with surveillance cameras being the most commonly employed. These cameras provide a video stream that typically lacks supplementary information. Extracting additional data from these streams could significantly enhance pedestrian behavior modeling and the automation of the monitoring process. A critical parameter in the analysis of pedestrian movement is their speed. The analytical method and the algorithm of pedestrians’ speed estimation based on the surveillance camera video are proposed. The first step of the proposed algorithm is object detection and tracking between frames. The second step is the speed estimation method, which is based on calculating the real-world distances and knowing camera parameters and distances in pixels on the resulting image. Implementation of the algorithm was tested on real videos and showed an error of about 0.04 m/s.