Research on moving object detection based on improved mixture Gaussian model

被引：21

作者：

Chen, Xiaorong ^{[1
]}

Xi, Chuanli ^{[1
]}

Cao, Jianghui ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai Key Lab Modern Opt Syst, Shanghai 200093, Peoples R China

来源：

OPTIK | 2015年 / 126卷 / 20期

基金：

中国国家自然科学基金;

关键词：

Gaussian mixture model; Object detection; Parameter estimation;

D O I：

10.1016/j.ijleo.2015.05.122

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

For the deficiency of the mixture Gaussian model (GMM), an improved GMM algorithm is proposed, which can be applied to moving object detection. Combined with codebook detection algorithm, the GMM model is initialized by video images pixels statistical mean and variance, and updated model using parameters confidence interval. The experiment results indicate that the proposed update model can detect moving objects in complex background effectively and has good robustness. (C) 2015 Elsevier GmbH. All rights reserved.

引用

页码：2256 / 2259

页数：4

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