Improved vehicle speed estimation using Gaussian mixture model and hole filling algorithm

Abstract

Vehicle speed estimation using Closed Circuit Television (CCTV) is one of the interesting issues in the field of computer vision. Various approaches are used to perform automation in vehicle speed estimation using CCTV. In this study, the use of Gaussian Mixture Model (GMM) for vehicle detection has been improved with the hole-filling method (HF). The speed estimation of the vehicles with various scenarios has been done, and gives the best estimation with the deviation of 7.63 Km/hr. GMM fusion with hole-filling algorithm combined with Pinhole models have shown the best results compared with results using other scenarios.