Handbook of Robust Low-Rank and Sparse Matrix Decomposition - Applications in Image and Video Processing (Hardcover)

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

General

Imprint:	Productivity Press
Country of origin:	United States
Release date:	May 2016
First published:	2016
Editors:	Thierry Bouwmans • Necdet Serhat Aybat • El-hadi Zahzah
Dimensions:	254 x 178 x 36mm (L x W x T)
Format:	Hardcover
Pages:	520
ISBN-13:	978-1-4987-2462-3
Categories:	Books > Science & Mathematics > Mathematics > Algebra > General Books > Computing & IT > Applications of computing > Image processing > General
LSN:	1-4987-2462-0
Barcode:	9781498724623

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