LRSLibrary

Version 1.7.0.0 (32.4 MB) by Andrews Cordolino Sobral
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
4.4
(7)
2.7K Downloads
Updated 15 Mar 2023
View License on GitHub

The LRSLibrary provides a collection of low-rank and sparse decomposition algorithms in MATLAB. The library was designed for background subtraction / motion segmentation in videos, but it can be also used or adapted for other computer vision problems. Currently the LRSLibrary contains a total of 103 matrix-based and tensor-based algorithms. The LRSLibrary was tested successfully in MATLAB R2013, R2014, R2015, and R2016 both x86 and x64 versions.
For more information, please see: https://github.com/andrewssobral/lrslibrary

Cite As

Andrews Cordolino Sobral (2024). LRSLibrary (https://github.com/andrewssobral/lrslibrary), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2013b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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algorithms/lrr/ADM

algorithms/lrr/ALM

algorithms/lrr/EALM

algorithms/lrr/FastLADMAP

algorithms/lrr/IALM

algorithms/lrr/LADMAP

algorithms/lrr/ROSL

algorithms/mc/FPC

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algorithms/mc/IALM-MC

algorithms/mc/IALM-MC/utils

algorithms/mc/LMaFit

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algorithms/mc/LMaFit/utils

algorithms/mc/LRGeomCG

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algorithms/mc/OR1MP/largescale_ops

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algorithms/rpca/ADM

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algorithms/td/RLRT/rpca

algorithms/td/RLRT/tc

algorithms/td/RLRT/utils

algorithms/td/RSTD

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algorithms/td/Tucker-ADAL

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algorithms/td/t-SVD

algorithms/ttd/3WD

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gui

libs/+lightspeed

libs/+lightspeed/@mutable

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libs/SVD

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utils

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Version Published Release Notes
1.7.0.0

Version 1.0.7: Code refactoring: process_matrix(), process_tensor(), run_algorithm_###() were excluded. A standard interface called run_algorithm was created. For each algorithm, there is a run_alg.m script for execution. Added 10 new algorithms.
1.4.0.0

Added three new algorithms.
1.3.0.0

Version 1.0.5: Added three new method categories, and fifteen new algorithms.
1.2.0.0

fix
1.1.0.0

fix
1.0.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.