Vision based vehicle counting at crowded intersections

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Date

2022-06-10

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UNIVERSITY of M'SILA

Abstract

Traffic congestion has a significant negative impact on the environment and on people, and one of the most important reasons is poor control of traffic signals. Vehicle counting in crowded intersections is a crucial element of any traffic optimization solution. In this work, we propose a computer vision based vehicle counting method. We adopts YOLO-v3 as vehicle de tector, we added a series of post-processing mechanisms to achieve robust vehicle counting. We created framework to asemi-utomatically generate a dedecated dataset for vehicle counting, this dataset can be later used as training data for new maching learning based solutions.

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Keywords

Computer vision; Intelligent traffic signal control system; Vehicle counting.

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