Vision based vehicle counting at crowded intersections - Benslimane, Echyma; Gherabi, Amira; Reporter: Ghemougui, Abdessettar (UNIVERSITY of M'SILA, 2022)
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.
Keywords: Computer vision; Intelligent traffic signal control system; Vehicle counting.