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机构地区:[1]长沙理工大学计算机与通信工程学院,长沙410114
出 处:《计算机工程与应用》2015年第14期198-202,共5页Computer Engineering and Applications
基 金:湖南省自然科学基金重点项目(No.10JJ2050)
摘 要:假定图像序列的背景图像已经获得,提出一种结合时空背景差和闭合轮廓拟合的运动人体目标检测算法。算法以较小的阈值获得当前帧的背景差分图像,并搜寻最大连通域为初始前景目标;构造加权高斯滤波器,提取初始前景目标边缘;拟合前景目标轮廓,提出2 bit区域选择法提取不连续弧段的端点,根据类间最小距离准则构造闭合轮廓,结合帧间差分提取最终前景轮廓,标注运动目标位置。仿真实验表明,该算法能准确提取出运动目标,并标注目标位置,在背景环境发生变化时同样可以准确检测到运动目标,具有较好的鲁棒性。A human detection method in video sequence based on background subtraction and closed contour fitting has been proposed if the background image has been acquired. Firstly, after having the background image, seek for the maximal connected domain of the original foreground objects; secondly, extract contour of the original foreground object through weighted gauss filters; finally, fit the closed contour of the original objects and extract them, a method of 2 bit area chosen has been proposed in order to seek for end points of one segment of a curve, then according to the criterion of the minimum distance between class structure closed contour, extract final foreground objects by using frame difference algorithm, and label the locations of the objects. The experimental results show that human detection algorithm in this paper can extract objects accurately and efficiently.
分 类 号:TN911.73[电子电信—通信与信息系统]
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