计算机技术与发展Issue(9)：27-30,4.DOI:10.3969/j.issn.1673-629X.2015.09.006
一种基于深度数据的高斯模型运动目标检测方法
A Gaussian Model Moving Target Detection Method Based on Depth Data
摘要
Abstract
The moving target detection systems based on image processing are sensitive to the light conditions of target scene. Present a new single Gauss model moving target detection method based on Kinect depth data,which can enhance robustness of the system in scene collection error. First,median filtering is used to process depth data. Then the single Gauss model is established for the depth data of target scene. The Gauss probability threshold is used to discriminate the collecting data of target scene and background parameters. Moving tar-get detection is achieved after morphological filtering. And real-time updating background parameters is a good way to make the model a-dapt to the change of scene. At last,experiments are performed. The proposed method has achieved well detection results.关键词
Kinect深度数据/单高斯模型/运动目标检测/形态学滤波Key words
Kinect depth data/single Gauss model/moving target detection/morphological filtering分类
信息技术与安全科学引用本文复制引用
杨磊,任衍允,蔡纪源..一种基于深度数据的高斯模型运动目标检测方法[J].计算机技术与发展,2015,(9):27-30,4.基金项目
国家自然科学基金资助项目(61005015) （61005015）
国家第三批博士后特别基金(201003280) （201003280）
上海市青年教师培育计划 （）
