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.
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Kowalczuk, Z., Frączek, S. (2017). System for tracking multiple trains on a test railway track. In: Mitkowski, W., Kacprzyk, J., Oprzędkiewicz, K., Skruch, P. (eds) Trends in Advanced Intelligent Control, Optimization and Automation. KKA 2017. Advances in Intelligent Systems and Computing, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-60699-6_20
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DOI: https://doi.org/10.1007/978-3-319-60699-6_20
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