| Issue |
EPJ Web Conf.
Volume 224, 2019
IV International Conference “Modeling of Nonlinear Processes and Systems” (MNPS-2019)
|
|
|---|---|---|
| Article Number | 04004 | |
| Number of page(s) | 7 | |
| Section | Machine Learning, Artificial Intelligence and High-Performance Computing | |
| DOI | https://doi.org/10.1051/epjconf/201922404004 | |
| Published online | 09 December 2019 | |
https://doi.org/10.1051/epjconf/201922404004
Method of Automated Detection of Traffic Violation with a Convolutional Neural Network
1
Don State Technical University, Institute of Service and Entrepreneurship, RU-346500, Shakhty, Rostov region, Russia
2
South Federal University, Institute of Radio Systems and Control, RU-347928, Taganrog, Rostov region, Russia
3
Department Telecommunications and Information Processing, Ghent University, B-9000, Ghent, Belgium
Published online: 9 December 2019
This article describes the relevance of developing methods and systems for detection photo-video violations of the Rules of the road. The proposed method includes several steps: 1) detecting of the three classes of objects on a video sequence (pedestrian crossing, a motor vehicle and a human on the pedestrian crossing; 2) tracking the trajectories of the vehicle and the human on the pedestrian crossing; 3) comparing the paths of the pedestrian and the vehicle and determining whether there has been a violation of the Rules of the road for a certain period of time. For real-time object detection, we used neural network YOLO V3.
© The Authors, published by EDP Sciences, 2019
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