Comparison of Moving Object Detection Algorithms

被引:0
作者
Zhu, Man [1 ]
Sun, Shuifa [1 ]
Han, Shuheng [1 ]
Shen, Hongying [1 ]
机构
[1] Three Gorges Univ, Inst Intelligent Vis & Image Informat, Yichang 443000, Hubei, Peoples R China
来源
2012 WORLD AUTOMATION CONGRESS (WAC) | 2012年
关键词
Single Gauss background modeling; Mixes the Gauss background modeling; Running Average background modeling;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
At present, object detection methods widely used are background subtraction and Frame difference. The core of background subtraction is background modeling. There are several commonly used background modeling algorithms, such as Single Gauss background modelling (SG), Mixed of Gaussian (MOG) background modelling, and Running Average (RA) background modelling. In the paper, firstly the background subtraction based on these three different background modelings, and the frame difference algorithm are systematic studied. Furthermore, the performance of all the algorithms is compared. Based on the comparison, a new objcet detection algorithm fused MOG and RA is proposed. This method effectively overcomes the detection failures, which are caused by illustrate sudden change in video detection, The experimental results prove effectiveness of the proposed method.
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页数:4
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