基于混合高斯模型与码本算法的前景目标检测

doi:10.3969/j.issn.1000-3428.2012.05.001

计算机工程 ›› 2012, Vol. 38 ›› Issue (5): 1-4. doi: 10.3969/j.issn.1000-3428.2012.05.001

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基于混合高斯模型与码本算法的前景目标检测

叶勇，管业鹏，李晶晶

(上海大学通信与信息工程学院，上海 200072)

收稿日期:2011-09-13 出版日期:2012-03-05 发布日期:2012-03-05
作者简介:叶勇(1986－)，男，硕士研究生，主研方向：数字图像处理，运动目标检测；管业鹏，教授、博士生导师；李晶晶，硕士研究生
基金资助:
国家自然科学基金资助项目(60872117)；上海大学创新基金资助项目(SHUCX112121)

Foreground Target Detection Based on Gaussian Mixture Model and Codebook Algorithm

YE Yong, GUAN Ye-peng, LI Jing-jing

(School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China)

Received:2011-09-13 Online:2012-03-05 Published:2012-03-05

摘要/Abstract

摘要：

提出一种基于混合高斯模型(GMM)与码本算法的前景目标检测方法。利用GMM进行背景图像建模并初步提取前景对象，对背景图像进行码本学习，将码本建模得到的前景对象与GMM得到的前景对象相融合，根据前后2次帧间差分得到前景对象的比例关系，自适应地更新高斯参数和扩展码字，得到前景对象目标。实验结果表明，该方法实时性好，可消除视频序列中的阴影和鬼影，提取完整的前景对象。

关键词: 前景检测, 阴影消除, 混合高斯模型, 码本算法, 帧间差分

Abstract:

This paper proposes a foreground moving object detection method based on Gaussian Mixture Model(GMM) and codebook. It uses GMM to extract initial foreground object, learns the background in use of codebook. It associates the foreground object obtained by GMM with the object of codebook foreground, updates the parameters of Gaussian model and codebook adaptively, according to the ratio between the foreground in 2 adjacent frames, and gets the moving object. Experimental results show that the method can eliminate the shadow of the video sequence and ghosting effectively, as well as obtain the entire foreground object in real time.

Key words: foreground detection, shadow elimination, Gaussian Mixture Model(GMM), codebook algorithm, inter-frame difference

中图分类号:

TP39

叶勇, 管业鹏, 李晶晶. 基于混合高斯模型与码本算法的前景目标检测[J]. 计算机工程, 2012, 38(5): 1-4.

XIE Yong, GUAN Ye-Feng, LI Jing-Jing. Foreground Target Detection Based on Gaussian Mixture Model and Codebook Algorithm[J]. Computer Engineering, 2012, 38(5): 1-4.

https://www.ecice06.com/CN/Y2012/V38/I5/1

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