Moving object extraction using the improved adaptive Gaussian mixture model and shadow detection model

被引:0
作者
Zeng, Zhigao [1 ]
Liu, Lihong [1 ]
Yi, Shengqiu [1 ]
Wen, Zhiqiang [1 ]
Yang, Fanwen [1 ]
Guan, Lianhua [1 ]
机构
[1] College of Computer and Communication, Hunan University of Technology, Hunan
来源
Journal of Information and Computational Science | 2015年 / 12卷 / 14期
基金
中国国家自然科学基金;
关键词
Adaptive Gaussian mixture model; Background modeling; HSV space; Moving objects;
D O I
10.12733/jics20106664
中图分类号
学科分类号
摘要
In order to overcome the shortcomings that the parameters of the adaptive Gaussian mixture model which is used for the background modeling update slowly, a new parameters learning mechanism is proposed in this paper. Then, according to the characteristics of the shadows of moving objects in HSV space, a background modeling algorithm is proposed using the improved adaptive Gaussian mixture model to extract the moving object. Simultaneously, in order to remove the shadow of the moving object, a shadow detection model is proposed in this paper. Experiments show that the shadow of moving objects can be eliminated effectively and the background modeling algorithm has good robustness. Copyright © 2015 Binary Information Press.
引用
收藏
页码:5515 / 5522
页数:7
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