Efficient and robust background modeling with dynamic mode decomposition

DOI10.1007/s10851-022-01068-0OpenAlexW4213454721MaRDI QIDQ2155166

Tim Krake, Daniel Weiskopf, Bernhard Eberhardt, Andrés Bruhn

Publication date: 15 July 2022

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-022-01068-0

zbMATH Keywords

spectral decompositiondynamic mode decompositionforeground detectionbackground modeling

Mathematics Subject Classification ID

Computer science (68-XX) Information and communication theory, circuits (94-XX)

Cites Work

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• Incremental principal component pursuit for video background modeling
• Decomposition into low-rank plus additive matrices for background/foreground separation: a review for a comparative evaluation with a large-scale dataset
• Robust PCA and subspace tracking from incomplete observations using \(\ell _0\)-surrogates
• Robust principal component pursuit via inexact alternating minimization on matrix manifolds
• Scalable Robust Matrix Recovery: Frank--Wolfe Meets Proximal Methods
• Background Modeling and Foreground Detection for Video Surveillance

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