A Fast Algorithm For A Weighted Low Rank Approximation
Abstract
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 ℓ1-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.
Publication Date
7-19-2017
Publication Title
Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
Number of Pages
93-96
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.23919/MVA.2017.7986798
Copyright Status
Unknown
Socpus ID
85027889136 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85027889136
STARS Citation
Dutta, Aritra and Li, Xin, "A Fast Algorithm For A Weighted Low Rank Approximation" (2017). Scopus Export 2015-2019. 7537.
https://stars.library.ucf.edu/scopus2015/7537