摘要
提出一种非参数前景背景分割方法.在将图像的强度信息与边界信息进行融合、提高运动目标检测的鲁棒性的同时,针对图像阴影区域的特性,通过阴影模型能够有效地检测阴影区域.实验结果表明该方法具有一定的实用性.
This paper presents a novel segmentation method based on a non-parametric background model that has the ability of modeling multi-model. Firstly, both the intensity and edge features are used to improve robustness of the foreground detection. Secondly, we also present an adaptive shadow detection model to find the accurate moving objects. The experiment results show that our proposed method is effective.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2005年第6期1278-1284,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家科技攻关计划课题奥运科技专项(2001BA904B08)
国家"八六三"高技术研究发展计划(2001AA231031)
国家重点基础研究发展规划项目(G1998030608)
关键词
分割
减背景
核密度估计
阴影消除
segmentation
background subtraction
kernel density estimation
shadow removal
