Improved Gaussian Mixture Model in Video Motion Detection

Abstract

As the classical Gaussian mixture model has some problems of not considering it self’s matching degree of Gaussian density functions, model updating and the background in real video motion detection, made improvements on the three aspects. Optimized Gaussian mixture model’s overall architecture and proposed an improved algorithm according to the analysis of the definition and disadvantages of classical Gaussian mixture model. Finally, through detailed experiment, the result showed: the improved Gaussian mixture model is faster in model convergence rate in video motion detection, can quickly adapt to the changes of background and greatly decreases the fall-out ratio