计算机工程与应用2016，Vol.52Issue(13)：195-200,6.DOI:10.3778/j.issn.1002-8331.1409-0016
改进的基于混合高斯模型的运动目标检测算法
Improved moving object detection method based on mixture Gaussian model
摘要
Abstract
Aim at the disadvantages of traditional mixture Gaussian model in moving object detection, an improved moving object detection method based on mixture Gaussian model is proposed. It solves the problem affected by the illumination mutations and the traditional frame difference is easily affected by double shadow which combines the improved mixture Gaussian model and four-frame subtraction. The improved mixture Gaussian model adjusts the numbers of the Gaussian distribution adaptively and improves the accuracy of the background description. This paper discusses the motion state of the object and different learning rates are set to improve the effect of slow-moving object detection. Experimental results show that the combined algorithm can detect moving object accurately and has better adaptability in complex scenes.关键词
混合高斯模型/运动目标检测/四帧差分/学习率Key words
mixture Gaussian model/moving object detection/four-frame subtraction/learning rate分类
信息技术与安全科学引用本文复制引用
郭伟,高媛媛,刘鑫焱..改进的基于混合高斯模型的运动目标检测算法[J].计算机工程与应用,2016,52(13):195-200,6.基金项目
国家自然科学基金(No.61103199) （No.61103199）
北京市自然科学基金(No.4112052). （No.4112052）
