{"repo":"andrewssobral/lrslibrary","free":true,"listed":false,"github":"https://github.com/andrewssobral/lrslibrary","clone":"git clone https://github.com/andrewssobral/lrslibrary.git","description":"Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos","language":"MATLAB","stars":886,"topics":["rpca","matrix-factorization","matrix-completion","tensor-decomposition","tensor","matlab","matrix","subspace-tracking","subspace-learning"],"license":null,"category":"chat-messaging","readme_excerpt":"Last Page Update: 29/07/2022 , Previous Page Update: 07/03/2020 Latest Library Version: 1.0.11 (see Release Notes for more info) LRSLibrary ---------- Low-Rank and Sparse tools for Background Modeling and Subtraction in Videos. The LRSLibrary provides a collection of low-rank and sparse decomposition algorithms in MATLAB. The library was designed for moving object detection in videos, but it can be also used for other computer vision and machine learning problems (for more information, please see here and here). Currently the LRSLibrary offers more than 100 algorithms based on matrix and tensor methods. The LRSLibrary was tested successfully in several MATLAB versions (e.g. R2014, R2015, R2016, R2017, on both x86 and x64 versions). It requires minimum R2014b . See also: Citation --------- If you use this library for your publications, please cite it as: Additional reference: Stargazers over time Install --- Just do the following steps: First, clone the repository: Then, open your MATLAB and run the following setup script: That's all! GUI --- The LRSLibrary provides an easy-to-use graphical user interface (GUI) for background modeling and subtraction in videos. First, run the setup script lrs setup (or run('C:/lrslibrary/lrs setup') ), then run lrs gui , and enjoy it! (Click in the image to see the video) Each algorithm is classified by its cpu time consumption with the following icons: The algorithms were grouped in eight categories: RPCA for Robust PCA, ST for Subspace Track","default_branch":null,"files":null,"tree":[],"storefront":"/r/andrewssobral","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/andrewssobral/lrslibrary/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}