光照突变场景中结合Phong模型的分层差分前景检测  

Hierarchical Subtraction Combining Phong Model for Foreground Detection in Sudden Illumination Changes Scenes

作　　者：曹倩霞[1,2] 罗大庸[1] 王正武[2] 

机构地区：[1]中南大学信息科学与工程学院,长沙410075 [2]电力与交通安全监控及节能技术教育部工程研究中心(长沙理工大学),长沙410004

出　　处：《计算机科学》2015年第2期283-286,共4页Computer Science

基　　金：国家自然科学基金项目(51278068);湖南省科技计划项目(2012GK3060);长沙理工大学电力与交通安全监控及节能技术教育部工程研究中心开放基金资助

摘　　要：针对前景检测中光照突变问题和非平稳背景扰动问题,提出一种块级-像素级分层背景差分结合Phong模型的前景检测方法。首先,利用块级Sigma-delta背景差分算法快速检测前景区域且有效处理非平稳背景,然后利用Phong模型对前景区域进行光照突变处理提取出粗目标,最后利用像素级Sigma-delta算法对粗目标执行像素级前景提纯操作和对背景进行更新。实验表明,该方法在光照突变场景中及非平稳背景中能鲁棒实现前景检测。To solve the problems of sudden illumination changes and non-stationary background disturbance during foreground detection,a foreground detection method combining block-level and pixel-level hierarchical background subtraction with Phong model was presented.First,the foreground areas are quickly detected and non-stationary background is effectively dealed with by using block-level Sigma-delta background subtraction algorithm.Then,the coarse targets are extracted from the foreground areas by using Phong model to deal with sudden illumination changes.Finally,the coarse targets are executed for pixel-level foreground refining operation and the background is updated by using pixel-level Sigma-delta algorithm.Experiments show that the method can achieve robust foreground detection in scenes with sudden illumination changes and non-stationary background.

关 键 词：前景检测 分层差分 光照变化 Sigma-delta滤波 PHONG模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]