文章基本信息

标题：Improved Gaussian Mixture Model in Video Motion Detection
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作者：Xie, Yong
期刊名称：Journal of Multimedia
印刷版ISSN：1796-2048
出版年度：2013
卷号：8
期号：5
页码：527-533
DOI：10.4304/jmm.8.5.527-533
语种：English
出版社：Academy Publisher
摘要：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
关键词：Matching Modal; Video Motion; Framework Optimization; Gaussian Mixture