南京邮电大学学报（自然科学版）2013，Vol.33Issue(2)：86-89,96,5.
基于低秩矩阵恢复的视频背景建模
Video Background Modeling Using Low-rank Matrix Recovery
摘要
Abstract
In this paper, a novel method is present based on low-rank matrix recovery, which can directly obtain background model as well as foreground objects from the video sequence. As the main computation of existing algorithms of low-rank matrix recovery is the singular value decomposition, most of which are time-consuming and not concise enough,the linear time SVD algorithm is introduced to the inexact augmented Lagrange multiplier method,and we get a more efficient background modeling algorithm. We test our algorithm on real video,and the experimental results show that our approach obtains good results and less time-consuming, compared to the exact and inexact augmented Lagrange multiplier method.关键词
低秩矩阵恢复/视频背景建模/增广拉格朗日乘子法/线性时间奇异值分解算法Key words
low-rank matrix recovery/video background modeling/augmented Lagrange multiplier method/ linear time SVD algorithm分类
信息技术与安全科学引用本文复制引用
杨敏,安振英..基于低秩矩阵恢复的视频背景建模[J].南京邮电大学学报（自然科学版）,2013,33(2):86-89,96,5.基金项目
江苏省自然科学基金(BK2011758)资助项目 （BK2011758）
