%0 Journal Article
%T A novel background Gaussian mixture model<br>新型背景混合高斯模型
%A Bai Xiangfeng
%A Li Aihu
%A Li Xilai
%A Li Renbing
%A <br>白向峰
%A 李艾华
%A 李喜来
%A 李仁兵
%J 中国图象图形学报
%D 2011
%I 
%X A deficit of classic Gaussian mixture model in background subtraction is the high computation cost. To solve this problem, a novel algorithm is proposed in this paper. A threshold parameter corresponding to the mean of deviation is utilized to judge whether a model matches the current pixel intensity. The new algorithm efficiently reduces the calculation burden of the operation of square and exponent with classical model; meanwhile, a non-linear weight updating approach is adopted, with the notion of sustain stationary time introduced in, and hence the quick converting of a relative long still object in scene into the background is achievable. Experimental results show that the new algorithm has significantly improved the calculation efficiency of background model.
%K object detection
%K background model
%K Gaussian mixture model
%K weight updating<br>目标检测
%K 背景模型
%K 混合高斯模型
%K 权值更新
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=EBF7289B0EEBDC9E1023A92163973104&yid=9377ED8094509821&vid=7801E6FC5AE9020C&iid=B31275AF3241DB2D&sid=88B4027FEBE4F5FF&eid=BB44F42BE8AE7430&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=1&reference_num=0