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The International Series in Video Computing

Robust Subspace Estimation Using Low-Rank Optimization

Theory and Applications

Authors: Oreifej, Omar, Shah, Mubarak

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  • Provides a comprehensive summary of the state-of-the-art methods and applications of Low-Rank Optimization
  • Reviews the latest approaches in a wide range of computer vision problems, including: Scene Reconstruction, Video Denoising, Activity Recognition, and Background Subtraction
  • Involves a self-complete and detailed description of the methods and theories which makes it ideal for graduate students looking for a comprehensive resource in this area
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eBook 79,72 €
price for Spain (gross)
  • ISBN 978-3-319-04184-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-319-04183-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-319-35248-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

Various fundamental applications in computer vision and machine learning require finding the basis of a certain subspace. Examples of such applications include face detection, motion estimation, and activity recognition. An increasing interest has been recently placed on this area as a result of significant advances in the mathematics of matrix rank optimization. Interestingly, robust subspace estimation can be posed as a low-rank optimization problem, which can be solved efficiently using techniques such as the method of Augmented Lagrange Multiplier. In this book, the authors discuss fundamental formulations and extensions for low-rank optimization-based subspace estimation and representation. By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate  how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.

Table of contents (8 chapters)

Table of contents (8 chapters)

Buy this book

eBook 79,72 €
price for Spain (gross)
  • ISBN 978-3-319-04184-1
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-319-04183-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 98,79 €
price for Spain (gross)
  • ISBN 978-3-319-35248-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Robust Subspace Estimation Using Low-Rank Optimization
Book Subtitle
Theory and Applications
Authors
Series Title
The International Series in Video Computing
Series Volume
12
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-04184-1
DOI
10.1007/978-3-319-04184-1
Hardcover ISBN
978-3-319-04183-4
Softcover ISBN
978-3-319-35248-0
Series ISSN
1571-5205
Edition Number
1
Number of Pages
VI, 114
Number of Illustrations
2 b/w illustrations, 39 illustrations in colour
Topics