A Fast Algorithm for a Weighted Low Rank Approximation

被引：0

作者：

Dutta, Aritra ^{[1
]}

Li, Xin ^{[1
]}

机构：

[1] Univ Cent Florida, Dept Math, Orlando, FL 32816 USA

来源：

PROCEEDINGS OF THE FIFTEENTH IAPR INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS - MVA2017 | 2017年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Matrix low rank approximation including the classical PCA and the robust PCA (RPCA) method have been applied to solve the background modeling problem in video analysis. Recently, it has been demonstrated that a special weighted low rank approximation of matrices can be made robust to the outliers similar to the l(1)-norm in RPCA method. In this work, we propose a new algorithm that can speed up the existing algorithm for solving the special weighted low rank approximation and demonstrate its use in background estimation problem.

引用

页码：93 / 96

页数：4

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