一种新的混合高斯模型的学习算法

混合高斯模型是背景对消中一种非常有效的方法.本文提出了一种有效的混合高斯模型的学习算法.与以前的方法不同在于:a.根据最大似然准则,在线的更新模型的参数;b.定义了遗忘因子和学习率因子,并根据它们实际的物理含义,得到了更一般的形式.运用这种算法对模拟视频数据和真实视频处理,结果表明,本文提出的学习算法无论在收敛速率,还是在准确性方面,都要优于以前的方法.

A Novel Learning Algorithm for Mixture Gaussian Models

Mixture Gaussian model is one of background subtraction methods.An effective and adaptive learning method to update parameters and increase learning rate is proposed in this paper.Comparing to previous work there are two innovations in the new algorithm.First,the parameters can be computed online through the recursive equations according to maximum likelihood rules.Second,forgetting factors and learning rate factors are redefined and their general and simple formulations are obtained by analyzing their practical functions. The new algorithm is applied to simulating data and actual video.The results show that the proposed learning algorithm excels the formers both in converging rate and accuracy.