采用自适应高斯混合方法为背景建模的难点是对背景模型的维持与更新。
Taking the method of adaptive Gaussian mixture method can make model for background meanwhile it is a difficult point to maintain and update background model.
该算法使用混合高斯模型表示粒子，在每个时刻的修正步骤之后，采用EM算法对粒子进行重新拟合。
It USES Gassian mixture model to represent particles and adopts EM algorithm to refit particles after correction step at each time.
用混合高斯模型得到运动人体的区域，通过卡尔曼滤波对人体进行跟踪，并利用人体的颜色信息进行识别。
Moving areas about human are segmented by using hybrid Gaussian model as background, tracked by Kalman filter, and recognized by using a color-based model.
应用推荐