基于混合高斯模型与码本算法的前景目标检测

提出一种基于混合高斯模型(GMM)与码本算法的前景目标检测方法。利用GMM进行背景图像建模并初步提取前景对象，对背景图像进行码本学习，将码本建模得到的前景对象与GMM得到的前景对象相融合，根据前后2次帧间差分得到前景对象的比例关系，自适应地更新高斯参数和扩展码字，得到前景对象目标。实验结果表明，该方法实时性好，可消除视频序列中的阴影和鬼影，提取完整的前景对象。

Foreground Target Detection Based on Gaussian Mixture Model and Codebook Algorithm

This paper proposes a foreground moving object detection method based on Gaussian Mixture Model(GMM) and codebook.It uses GMM to extract initial foreground object,learns the background in use of codebook.It associates the foreground object obtained by GMM with the object of codebook foreground,updates the parameters of Gaussian model and codebook adaptively,according to the ratio between the foreground in 2 adjacent frames,and gets the moving object.Experimental results show that the method can eliminate the shadow of the video sequence and ghosting effectively,as well as obtain the entire foreground object in real time.