Using existing surveillance infrastructure to monitor pedestrians on pedestrian bridges: aproof of concept

[摘要] ENGLISH ABSTRACT: Due to the high number of pedestrians involved in crashes along the freeways in South Africa, there is a need for authorities to monitor pedestrians using the freeways in order to gain valuable mobility information. As South Africa is a developing country, existing surveillance infrastructuremust be used to its fullest extent.This work presents a proof of concept that existing surveillance infrastructure can be used to implement a pedestrian monitoring system. The system willmonitorpedestrians using pedestrian bridges along the freeways, and will collect pedestrian mobility information, such as the direction and relative speed of movement. The system thus aims to contribute to pedestrian safety in South Africa.A cascade classifier is trained with surveillance footage collected from SANRAL using AdaBoost and the use of approximated image scales. It is shown that the detectors need to be trained specifically for a scene/camera using footage from thatscene/camera in order to compete with modern pedestrian detection applications.The Integral Channel Features (ICF) detection method, which incorporated HOG andcolour channels, is used in this thesis as it is easily implemented and achieved stateof-the-art performance. A graphical user interface is created to run the training and detection phases as this removes the user formthe complicated back-end.The detected pedestrians are tracked using parametric tracking methods such as a Kalman filter, and supplementary track management functions. The trackedpedestrians are automatically counted and compared to pedestrian counts done by hand. The results show that the automatic pedestrian counting system achieved anaccuracy of more than 90%. A user friendly verification user interface is created to allow for themeaningful representation the pedestrian mobility results.A further analysis of the pedestrian mobility information collected, shows that the peak hour pedestrian traffic in the morning is between 06:30-07:30, and in theafternoon between 17:00-18:00. The data also shows that pedestrian traffic in the morning is highest towards the CDB, and in the afternoon is away from the CBD. It can also be seen that pedestrians move on average 10% faster towards the CBD.The results is proof that the pedestrian monitoring system using existing lowresolutionsurveillance infrastructure on pedestrian bridges can be used to obtain state-of-the-art performance. Thus it demonstrates that the system achieves the goalsset, and that the application of such a system is to be kept in mind during future infrastructure installations and upgrades.

[发布机构] Stellenbosch University