System for tracking multiple trains on a test railway track

Abstract

Several problems may arise when multiple trains are to be tracked using two IP camera streams. In this work, real-life conditions are simulated using a railway track model based on the Pomeranian Metropolitan Railway (PKM). Application of automatic clustering of optical flow is investigated. A complete tracking solution is developed using background subtraction, blob analysis, Kalman filtering, and a Hungarian algorithm. In total, six morphological, convolutional and non-linear filtering methods are compared in sixty-three combinations. Accuracy and performance of the system are evaluated, and the obtained results are analysed and commented on.