Low-Rank Models in Visual Analysis
Theories, Algorithms, and Applications
Series: Computer Vision and Pattern Recognition;
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39 450 Ft
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Product details:
- Publisher Elsevier Science
- Date of Publication 5 June 2017
- ISBN 9780128127315
- Binding Paperback
- No. of pages260 pages
- Size 229x152 mm
- Weight 430 g
- Language English 0
Categories
Long description:
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.
MoreTable of Contents:
1. Introduction
2. Linear Models
3. Nonlinear Models
4. Optimization Algorithms
5. Representative Applications
6. Conclusions
