Compressed Dynamic Mode Decomposition for Background Modeling
Abstract
We introduce the method of compressed dynamic mode decomposition (cDMD) for background modeling. The dynamic mode decomposition (DMD) is a regression technique that integrates two of the leading data analysis methods in use today: Fourier transforms and singular value decomposition. Borrowing ideas from compressed sensing and matrix sketching, cDMD eases the computational workload of high resolution video processing. The key principal of cDMD is...
Paper Details
Title
Compressed Dynamic Mode Decomposition for Background Modeling
Published Date
Dec 14, 2015
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