Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow

Akhtar, Muhammad Moin and Li, Yong and Zhong, Lei and Ansari, Ayesha (2020) Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow. Journal of Engineering Research and Reports, 15 (2). pp. 19-27. ISSN 2582-2926

[thumbnail of Akhtar1522020JERR59118.pdf] Text
Akhtar1522020JERR59118.pdf - Published Version

Download (1MB)

Abstract

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.

Item Type: Article
Subjects: Apsci Archives > Engineering
Depositing User: Unnamed user with email support@apsciarchives.com
Date Deposited: 17 Mar 2023 06:21
Last Modified: 18 Sep 2023 11:45
URI: http://eprints.go2submission.com/id/eprint/485

Actions (login required)

View Item
View Item