Illegal Parking Detection Using Gaussian Mixture Model and Kalman Filter
Rami Akhawaji, Mohamed Sedky, Abdel‐Hamid Soliman · 2017
Automatic analysis of videos for traffic monitoring has been an area of significant research in the recent past. In this paper, we proposed a system to detect and track illegal vehicle parking using Gaussian Mixture Model and Kalman Filter. i-LIDS dataset is used to test and evaluate the algorithm by comparing the results with the ground truth provided, we have tested the system using 4 full videos from i-LIDS to detect parked vehicle whiten specific area. Region of interest has been used to detect Vehicle parks in a no parking zone over sixty seconds and remains stationary.Within the scope of this work, we highlighted the components of an automated traffic surveillance system, including background modeling, foreground extraction, Kalman filter and Gaussian mixture model.