EXTRACTING MICROSCOPIC PEDESTRIAN CHARACTERISTICS FROM VIDEO DATA : RESULTS FROM EXPERIMENTAL RESEARCH INTO PEDESTRIAN WALKING BEHAVIOR

This paper discusses an approach to extract individual pedestrian data from digital video footage. In this specific case, the footage was collected during a large scale walking experiment performed at the Delft University of Technology. A group of approximately 80 pedestrians conducted different tests, while being observed using a video camera mounted at the ceiling of the hall. In the first phase of the pedestrian tracking process, different image processing operations, such as radiometric correction and correction for lens distortion are applied. Next, the pedestrians are detected by identifying the special colored caps the pedestrians were wearing during the experiment. This detection occurs in a special zone where conditions are such that pedestrian detection is optimal. Next pedestrian tracking is achieved by application of a newly developed tracking technique. This is achieved by minimizing the so-called merit-function. A Kalman filter is applied to reduce the errors made during tracking. The paper concludes by showing some of the tracking results, and accuracy estimates. It turns out that the pedestrian trajectories can be determined with high accuracy. Also, some interesting findings pertaining to the behavior of pedestrians are reported