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Yasunari Yokota
Department of Electrical, Electronics and Computer Engineering, Faculty of Engineering, Gifu University
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Detection of Congested Traffic Flow during Road Construction using Improved Background Subtraction with Two Levels RoI Definition Yoanda Alim Syahbana; Yasunari Yokota
International ABEC 2021: Proceeding International Applied Business and Engineering Conference 2021
Publisher : International ABEC

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Abstract

This study is aimed to detect traffic congestion that may occur during roadblocks of road construction. We improved the background subtraction method by considering Region of Interest (RoI) in the video frame to detect the congestion. The proposed method has experimented with video test material that shows traffic condition in the road construction site. The performance of the proposed method is evaluated using Confusion Matrix by comparing the result of the experiment with ground truth obtained visually. As a benchmarking process, the performance is also compared with the conventional background subtraction method. The result shows that the proposed method can achieve an accuracy of 83.2% for video from the first camera and 82.3% for video from the second camera. In comparison, the conventional background subtraction method only achieves 49.8% for video from the first camera and 0% for video from the second camera. Based on this evaluation, the proposed method can support implementation of efficient traffic control using adaptive traffic light that is equipped with camera.
Co-Authors Yoanda Alim Syahbana