Handbook of Robust Low-Rank and Sparse Matrix Decomposition

This handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It offers a framework for computer vision applications, including image processing and video surveillance, and describes many methods and algorithms to tackle different formulation problems. It also presents an introduction for beginners that reviews various decompositions, loss functions, optimization problems, and solvers. Software demos, datasets, and codes are available online.