Robust Subspace Learning
Handbook on Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing, CRC Press, Taylor and Francis Group, December 2015.
Low-Rank Matrix Recovery and Completion via Convex Optimization (Perception and Decision Lab., University of Illinois, USA)
LRS Library (A. Sobral, L3i, Univ. La Rochelle, France)
The LRSLibrary provides a collection of low-rank and sparse decomposition algorithms in MATLAB. The library was designed for motion segmentation in videos, but it can be also used or adapted for other computer vision. Currently the LRSLibrary contains a total of 72 matrix-based and tensor-based algorithms. The LRSLibrary was tested successfully in MATLAB R2013b both x86 and x64 versions.
Compressive Sensing Resources (Rice University, USA)
Handbook on Background Modeling and Foreground Detection for Video Surveillance, CRC Press, Taylor and Francis Group, July 2014.
Background Subtraction Website (T. Bouwmans, Lab. MIA, Univ. La Rochelle, France)
(See the Section « Recent Background Modeling » for Background Modeling via Robust Subspace Learning via Decomposition into Low-rank plus Additive Matrices)
BGS Library (A. Sobral, L3i, Univ. La Rochelle, France)
The BGSLibrary provides an easy-to-use C++ framework based on OpenCV to perform background subtraction (BGS) in videos. The BGSLibrary compiles under Linux, Mac OS X and Windows. The source code is available under GNU GPL v3 license, the library is free and open source for academic purposes.
Structure for Motion
VisualSFM (C. Wu, Google, USA)
VisualSFM is a GUI application for 3D reconstruction using structure from motion (SFM).