Based on Improved Adaptive Background Mixture Gaussian Model Vehicle Detection
Abstract：An improved adaptive background mixture Gaussian model has been proposed under the conditions of static camera motion detection problem of vehicles.Initially,it determines the moving target region by three frame difference methods,updates the algorithm by regional background to generate the initial background image.Then on the basis of adaptive Gaussian mixture background model put forward by Stauffer,it integrates the frame difference and background difference methods to determine moving target zone and background zone.It sets different learning rates according to background zone and the moving target zone to update the background model and it raises the convergence speed.The experimental results show that,compared with traditional detection methods,the improved algorithm can more quickly initialize background model and efficiently detect moving vehicles and also it has strong robustness and good adaptability.
Keywords：Gaussian mixture modelthree frame differencebackground modelingvehicle detection
Publication Date：2012-01-01
Online Publishing Date：2026-08-28(First online date of this platform, not the publication date of the document)
Pages：5( 37-41 )