Abstract
In this paper there are proposed methods and algorithms supporting city traffic controllers in effective perception and analysis of the visual information from the public transport monitoring system implemented in the City of Warsaw. To achieve this goal, public transport vehicles must be recognised and tracked in camera view. In this work, we describe a structure and give preliminary results for the detection and tracking system proposed. The algorithms discussed in this paper uses background subtraction to extract moving vehicles from the scene and the classification system to reject objects that are not city buses. Furthermore, a custom tracking module is utilized to enable labeling of city buses instances. During the test performed in the City of Warsaw the system was able to successfully detect 89% bus instances giving less than 15% erroneous detections.
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This research has been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 688380 VaVeL: Variety, Veracity, VaLue: Handling the Multiplicity of Urban Sensors.
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Wilkowski, A., Mykhalevych, I., Luckner, M. (2020). City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-030-13273-6_31
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