City Bus Monitoring Supported by Computer Vision and Machine Learning Algorithms
Authors:
- Artur Wilkowski,
- Marcin Luckner,
- Ihor Mykhalevych
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 the 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 labelling 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.
- Record ID
- WUTdfa391dde7184facba6258a88efbde84
- Author
- Pages
- 326-336
- Publication size in sheets
- 0.50
- Book
- Szewczyk Roman*, Roman Szewczyk Zieliński Cezary, Cezary Zieliński Kaliczyńska Małgorzata Małgorzata Kaliczyńska (eds.): Automation 2019: Progress in Automation, Robotics and Measurement Techniques, Advances in Intelligent Systems and Computing, vol. 920, 2020, Cham, Switzerland, Springer, 727 p., ISBN 978-3-030-13272-9. DOI:10.1007/978-3-030-13273-6 Opening in a new tab
- Keywords in Polish
- Widzenie maszynowe, Detekcja, Śledzenie, nadzór ruchu
- Keywords in English
- Computer vision, detection, tracking, traffic monitoring
- Abstract in Polish
- W pracy opisano eksperyment dotyczący automatycznego rozpoznania autobusów komunikacji miejskiej na zapisie wideo. Problem polagał na wyodrębnieniu pojazdów z tła, a następnie na odróżnieniu autobusów miejskich od samochodów osobowych i innych autobusów. Osiągnięto skuteczność 85% w rozpoznawaniu autobusów przy 15% błednych rozpoznań innych pojazdów.
- DOI
- DOI:10.1007/978-3-030-13273-6_31 Opening in a new tab
- URL
- https://link.springer.com/chapter/10.1007/978-3-030-13273-6_31 Opening in a new tab
- Language
- (en) English
- Score (nominal)
- 20
- Score source
- publisherList
- Score
- = 20.0, 05-05-2022, ChapterFromConference
- Publication indicators
- = 0; = 0
- Uniform Resource Identifier
- https://repo.pw.edu.pl/info/article/WUTdfa391dde7184facba6258a88efbde84/
- URN
urn:pw-repo:WUTdfa391dde7184facba6258a88efbde84
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or PerishOpening in a new tab system.