Mathematical Optimization in Computer Graphics and Vision
eBook - PDF

Mathematical Optimization in Computer Graphics and Vision

  1. 304 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Mathematical Optimization in Computer Graphics and Vision

About this book

Mathematical optimization is used in nearly all computer graphics applications, from computer vision to animation. This book teaches readers the core set of techniques that every computer graphics professional should understand in order to envision and expand the boundaries of what is possible in their work.Study of this authoritative reference will help readers develop a very powerful tool- the ability to create and decipher mathematical models that can better realize solutions to even the toughest problems confronting computer graphics community today.- Distills down a vast and complex world of information on optimization into one short, self-contained volume especially for computer graphics- Helps CG professionals identify the best technique for solving particular problems quickly, by categorizing the most effective algorithms by application- Keeps readers current by supplementing the focus on key, classic methods with special end-of-chapter sections on cutting-edge developments

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Yes, you can access Mathematical Optimization in Computer Graphics and Vision by Luiz Velho,Paulo Carvalho,Jonas Gomes,Luiz de Figueiredo in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Graphics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Front Cover
  2. Mathematical Optimization in Computer Graphics and Vision
  3. Copyright Page
  4. Table of Contents
  5. List of Figures
  6. Preface
  7. Acknowledgments
  8. Chapter 1. Computer Graphics
  9. Chapter 2. Optimization: An Overview
  10. Chapter 3. Optimization and Computer Graphics
  11. Chapter 4. Variational Optimization
  12. Chapter 5. Continuous Optimization
  13. Chapter 6. Combinatorial Optimization
  14. Chapter 7. Global Optimization
  15. Chapter 8. Probability and Optimization
  16. Index