Enhanced the moving object detection and object tracking for traffic surveillance using RBF-FDLNN and CBF algorithm

作者：

Highlights：

• To detect moving object using RBF-FDLNN and CFR algorithm.

• To detect and classifies moving object using proposed RBF-FDLNN classifier in the given video frame.

• Comparative analysis of our model with other similar contemporary research works.

摘要

•To detect moving object using RBF-FDLNN and CFR algorithm.•To detect and classifies moving object using proposed RBF-FDLNN classifier in the given video frame.•Comparative analysis of our model with other similar contemporary research works.

论文关键词：Traffic Surveillance,Object detection,Background Removal,Improved Gaussian Mixture Model (IGMM),Radial Basis Function based Filtered Deep Learning neural network (RBF-FDLNN),Genetic Cross Search (GCS)

论文评审过程：Received 8 May 2021, Revised 24 November 2021, Accepted 25 November 2021, Available online 30 November 2021, Version of Record 9 December 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116306