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LRSLibrary is a MATLAB library offering a broad collection of low-rank plus sparse decomposition algorithms, primarily aimed at background/foreground modeling from videos (background subtraction) and related computer vision tasks. Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine learning problems beyond video. Large algorithm collection: > 100 matrix- and tensor-based low-rank + sparse methods. Open-source license, documentation and references included.
Features
- Large algorithm collection: > 100 matrix- and tensor-based low-rank + sparse methods
- Support for background modeling / foreground detection in videos
- Demonstration scripts / example usage
- Compatibility across MATLAB versions (tested in R2014–R2017)
- Both matrix- and tensor-based decompositions
- Open-source license, documentation and references included
Project Samples
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Machine LearningFollow LRSLibrary
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