Overview
- Covers the most state-of-the-art topics of sparse and low-rank modeling
- Examines the theory of sparse and low-rank analysis to the real-world practice of sparse and low-rank analysis
- Contributions from top experts voicing their unique perspectives included throughout
- Includes supplementary material: sn.pub/extras
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Editors and Affiliations
About the editor
Bibliographic Information
Book Title: Low-Rank and Sparse Modeling for Visual Analysis
Editors: Yun Fu
DOI: https://doi.org/10.1007/978-3-319-12000-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-11999-1Published: 19 November 2014
Softcover ISBN: 978-3-319-35567-2Published: 01 October 2016
eBook ISBN: 978-3-319-12000-3Published: 30 October 2014
Edition Number: 1
Number of Pages: VII, 236
Number of Illustrations: 15 b/w illustrations, 51 illustrations in colour
Topics: Image Processing and Computer Vision, Signal, Image and Speech Processing, Computer Imaging, Vision, Pattern Recognition and Graphics
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