Improved adaptive Gaussian mixture model for background subtraction

被引：1501

作者：

Zivkovic, Z ^{[1
]}

机构：

[1] Univ Amsterdam, Intelligent & Autonomous Syst Grp, Amsterdam, Netherlands

来源：

PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 | 2004年

关键词：

D O I：

10.1109/ICPR.2004.1333992

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Background subtraction is a common computer vision task. We analyze the usual pixel-level approach. We develop an efficient adaptive algorithm using Gaussian mixture probability density. Recursive equations are used to constantly update the parameters and but also to simultaneously select the appropriate number of components for each pixel.

引用

页码：28 / 31

页数：4

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