计算机工程与应用Issue(18)：209-213,5.DOI:10.3778/j.issn.1002-8331.1309-0165
基于边缘前景的混合高斯模型目标检测
Gaussian mixture model moving object detection based on foreground of edge images
摘要
Abstract
Gaussian mixture model has been widely used for background modeling. However, the detection result is easily affected by noise and illumination mutation. In order to solve this problem, this paper proposes to combine the improved Gaussian mixture model with edge information. Once the method of three frame difference detects changes of the environ-ment, the learning rate will be adjusted adaptively. The improved Gaussian mixture model is applied to extracting edge images and foreground images of moving objects. After dilating edge images, the result is obtained by computing the intersection of edge images and foreground images, and filling the hollow part based on the information of optical flow. Experimental results indicate that the proposed method has great capacity in restraining noise and dealing with illumination mutation, and improves the performance of object detection. It is more efficient than the traditional method.关键词
混合高斯模型/边缘检测/目标检测/三帧差分/光流法Key words
Gaussian mixture model/edge detection/object detection/three frame difference/optical flow分类
信息技术与安全科学引用本文复制引用
郭伟,刘鑫焱,肖振久..基于边缘前景的混合高斯模型目标检测[J].计算机工程与应用,2015,(18):209-213,5.基金项目
国家自然科学基金（No.61103199）；北京市自然科学基金（No.4112052）。 （）
