Robust PCA Using Matrix Factorization for Background/Foreground Separation

Robust PCA Using Matrix Factorization for Background/Foreground Separation

Background/foreground separation has become an inevitable step in numerous image/video processing applications, such as image/video inpainting, anomaly detection, motion segmentation, augmented reality, and so on. Recent low-rank based approaches, such as robust principal component analysis separati...

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Bibliographic Details
Main Authors: Shuqin Wang, Yongli Wang, Yongyong Chen, Peng Pan, Zhipeng Sun, Guoping He
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Background/foreground separation
matrix factorization
robust PCA
Online Access:https://ieeexplore.ieee.org/document/8326698/

Internet

https://ieeexplore.ieee.org/document/8326698/

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