Determining Vehicle Turn Counts at Multiple Intersections by Separated Vehicle Classes Using CNNs

In our submission to the NVIDIA AI City Challenge 2020, we address the problem of counting vehicles by their class at multiple intersections. Our solution is based on counting by tracking principle using convolutional neural networks in detection and tracking steps of the proposed method. We have ac...

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Bibliographic Details
Published in:	2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pp. 2544 - 2549
Main Authors:	Folenta, Jan, Spanhel, Jakub, Bartl, Vojtech, Herout, Adam
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-06-2020
Subjects:	Artificial intelligence Automobiles Cameras Detectors Task analysis Trajectory Urban areas
Online Access:	Get full text
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Summary:	In our submission to the NVIDIA AI City Challenge 2020, we address the problem of counting vehicles by their class at multiple intersections. Our solution is based on counting by tracking principle using convolutional neural networks in detection and tracking steps of the proposed method. We have achieved 6th place on the dataset part A of Track 1 with score S1 Total = 0.8829, (mwRMSE = 4.3616, S1 Effectiveness = 0.9094, S1 Efficiency = 0.8212). The proposed solution was placed at sixth place in the overall ranking on dataset part A.
ISSN:	2160-7516
DOI:	10.1109/CVPRW50498.2020.00306