Pedestrian trajectories are used to learn about human behavior in public space and the impact of spatial features on pedestrian flows. Currently, these trajectories are collected manually, with self-tracking devices, or with video cameras. Even when trajectories are obtained using computational techniques, such as using computer vision to trace them in space, these datasets are not made available for reproducibility or comparative studies between different locations. To close this gap, this paper makes available the data of pedestrian trajectories collected in 39 European squares. Firstly, we summarize the data collection process which was based on collecting footage from publicly available webcams. Secondly, we describe the process of trajectory extraction entailing object detection, tracking, and georeferencing. Lastly, we describe the data cleaning and validation steps that lead to the final dataset. The dataset ultimately includes 348,300 pedestrian trajectories extracted from 193 hours of video footage, collected at different times of the day, during working days and weekends, and during the Spring and Summer season.
Wolff et al. (Tue,) studied this question.