An intelligent tool for the automated evaluation of pedestrian simulation

One of the most cumbersome tasks in the implementation of an accurate pedestrian model is the calibration and fine tuning based on real life experimental data. Traditionally, this procedure employs the manual extraction of information about the position and locomotion of pedestrians in multiple videos. The paper in hand proposes an automated tool for the evaluation of pedestrian models. It employees state of the art techniques for the automated 3D reconstruction, pedestrian detection and data analysis. The proposed method constitutes a complete system which, given a video stream, automatically determines both the workspace and the initial state of the simulation. Moreover, the system is able to track the evolution of the movement of pedestrians. The evaluation of the quality of the pedestrian model is performed via automatic extraction of critical information from both real and simulated data.