Accurate dynamic scene model with double-layer Gaussian mixture - art. no. 67864M

被引：0

作者：

Yang, Hong ^{[1
]}

Tan, Yihua ^{[1
]}

Tian, Jinwen ^{[1
]}

Liu, Jian ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Inst Pattern Recognit & Artificial Intelligence, State Key Lab Multispectral Informat Proc Technol, Wuhan 430074, Peoples R China

来源：

MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2 | 2007年 / 6786卷

关键词：

Gaussian mixture model; background subtraction; moving object detection;

D O I：

10.1117/12.752761

中图分类号：

TP7 [遥感技术];

学科分类号：

081102 ; 0816 ; 081602 ; 083002 ; 1404 ;

摘要：

Gaussian mixture model is a popular method to model dynamic scenes viewed by a fixed camera. However, we found that it is not a trivial problem for each component of Gaussian mixture to learn the accurate parameters for complex pixels. Furthermore, traditional method of Gaussian mixture has to make a tradeoff between system stability and convergence rate. We developed a mechanism of double-layer Gaussian mixture model for moving object detection from dynamic scenes, which can improve the convergence rate without compromising the system stability. Additionally, temporal consistency of variances was taken into account to alleviate camouflage problems in the process of detection.

引用

页码：M7864 / M7864

页数：7

共 11 条

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