Low-Rank Models in Visual Analysis
  • Release Date : 06 June 2017
  • Publisher : Academic Press
  • Genre : Computers
  • Pages : 260 pages
  • ISBN 13 : 9780128127322
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Download or read book entitled Low-Rank Models in Visual Analysis by author: Zhouchen Lin which was release on 06 June 2017 and published by Academic Press with total page 260 pages . This book available in PDF, EPUB and Kindle Format. Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which Low-rank models are highly useful in practice (both linear and nonlinear models), how to solve low-rank models efficiently, and how to apply low-rank models to real problems. Presents a self-contained, up-to-date introduction that covers underlying theory, algorithms and the state-of-the-art in current applications Provides a full and clear explanation of the theory behind the models Includes detailed proofs in the appendices

Skeletonization

Skeletonization

Author : Punam K Saha,Gunilla Borgefors,Gabriella Sanniti di Baja
Publisher : Academic Press
Genre : Technology & Engineering
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