The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLII-2/W13
05 Jun 2019
 | 05 Jun 2019


C. Koetsier, S. Busch, and M. Sester

Keywords: Trajectory Extraction, Deep Learning, Surveillance Video Analysis, Trajectory Analysis

Abstract. The environment of the vehicle can significantly influence the driving situation. Which conditions lead to unsafe driving behaviour is not always clear, also not to a human driver, as the causes might be unconscious, and thus cannot be revealed by expert interviews. Therefore, it is important to investigate how such situations can be reliably detected, and then search for their triggers. It is conceivable that such insecure situations (e.g. near-accidents, U-turns, avoiding obstacles) are reflected, for example, as anomalies in the movement trajectories of road users.

Collecting real world traffic data in driving studies is very time consuming and expensive. However, a lot of roads or public areas are already monitored with video cameras. In addition, nowadays more and more of such video data is made publicly available over the internet so that the amount of free video data is increasing. This research will exploit the use of such kind of opportunistic VGI. In the paper the first step of an automatic analysis are presented, namely: to introduce a real time processing pipeline to extract road user trajectories from surveillance video data.