Moving Object Detection Based on Improved Background Updating Method for Gaussian Mixture Model

被引:0
|
作者
Wen, Wu [1 ,2 ]
Jiang, Tao [1 ]
Gou, Yu Fang [3 ]
机构
[1] Chongqing Univ Posts & Telecommun, Res Ctr Applicat New Commun Technol, Chongqing 400065, Peoples R China
[2] Chongqing Informat Technol Designing Co Ltd, Chongqing 400065, Peoples R China
[3] Chongqing normal Univ, Chongqing 401331, Peoples R China
来源
MODERN TECHNOLOGIES IN MATERIALS, MECHANICS AND INTELLIGENT SYSTEMS | 2014年 / 1049卷
关键词
Gaussian mixture model; illumination mutation; Frame difference; short-stayed object;
D O I
10.4028/www.scientific.net/AMR.1049-1050.1561
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
An effective improvement method was put forward caused by the traditional Gaussian mixture model has poor adaptability to illumination mutation. When illumination mutation is detected, improved Frame difference could detect the foreground region and background region, and then adopts a new replacing update methods to the Gaussian distribution with the least weights of Gaussian mixture background models in different regions. The experimental results show that improved method makes Gaussian mixture model can quickly adaptive to the light mutation, and exactly detect the moving object.
引用
收藏
页码:1561 / +
页数:2
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