Dynamic mode decomposition via dictionary learning for foreground modeling in videos
作者：
Highlights：
• Dynamic mode decomposition (DMD) via dictionary learning.
• Effective extraction of foreground objects in videos.
• Analysis of local level dynamics of different areas in videos.
• Reconstruction of video patches via learned dictionary in DMD for denoising.
• Minimize reconstruction error in standard DMD by dictionary learning method.
摘要
•Dynamic mode decomposition (DMD) via dictionary learning.•Effective extraction of foreground objects in videos.•Analysis of local level dynamics of different areas in videos.•Reconstruction of video patches via learned dictionary in DMD for denoising.•Minimize reconstruction error in standard DMD by dictionary learning method.
论文关键词：Dynamic mode decomposition,Nonlinear dynamical system,Dictionary learning,Object extraction,Background modeling,Foreground modeling
论文评审过程：Received 4 December 2019, Revised 7 May 2020, Accepted 17 June 2020, Available online 23 June 2020, Version of Record 25 June 2020.
论文官网地址：https://doi.org/10.1016/j.cviu.2020.103022
