Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow
Muhammad Moin Akhtar, Yong Li, Lei Zhong, Ayesha Ansari
Journal of Engineering Research and Reports · pp. 19–27 · Published 4 Aug 2020
10.9734/jerr/2020/v15i217141Abstract
Vehicle detection, tracking, and counting play a significant role in traffic surveillance and are principle applications of the Intelligent Transport System (ITS). Traffic congestion and accidents can be prevented with an adequate solution to problems. In this paper, we implemented different image processing techniques to detect and track the moving vehicle from the videos captured by a stationary camera and count the total number of vehicles passed by. The proposed approach consists of an optical flow method with a Gaussian mixture model (GMM) to obtain an absolute shape of particular moving objects which improves the detection performance of moving targets.
Cited by 4
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Alabi Abdulkadir, O. Adegbola, Peter Olalekan Idowu · 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON) · 2022
Oluwole Abiodun Adegbola, Abdulkadir Zinat Alabi, Peter Olalekan Idowu · Asian Journal of Research in Computer Science · 2022
K. Hemalakshmi, A. Muthukumaravel · Advances in Computational Intelligence and Robotics · 2024
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