Review:
The definitive one-stop reference on mathematical optimization techniques for computer graphics
From the Back Cover:
Mathematical Optimization of Computer Graphics and Vision
Luiz Velho, Paulo Cezar Pinto Carvalho,
Jonas Gomes, Luiz Henrique de Figueiredo
Mathematical optimization is deeply pervasive in the vast majority of graphical applications. To study all available methodologies would be the work of a lifetime, however, there is a 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.
This authoritative reference is a consolidated guide to the seminal techniques of mathematical optimization as applied to computer graphics and vision.
It provides a conceptual overview of the key problems in computer graphics and explains the core mathematical models that can be used to solve them, demonstrating their pivotal importance.
It aids readers in finding the right optimization technique for a specific application by providing combinatorial, continuous, variational, and global optimization methods for applications including:
Camera Calibration
Color Correction
Geometric Modeling
Animation
Visualization
Coding and Compression
Image Processing
Computer Vision
Image and Color Quantization
Level of Detail Computation
Interactive Visualization
Minimum Paths in Maps
Surface Reconstruction from Sections
Algorithms, such as Newton methods, linear programming, conjugate gradient and sequential quadratic programming, Dijkstra, and Branch-and-bound, are explained alongside strategies for devising good algorithms. Special emphasis is given to the subtle relationships between probability theory and mathematical optimization. Cutting-edge research is discussed in a section at the end of every chapter, accompanied by targeted references to further reading.
Professionals exploring computer vision, geometric modeling, visualization, animation, and image processing will all benefit from the insights of the authors, who are renowned researchers from IMPA, the Brazilian National Institute for Pure, and Applied Mathematics.|Mathematical Optimization of Computer Graphics and Vision
Luiz Velho, Paulo Cezar Pinto Carvalho,
Jonas Gomes, Luiz Henrique de Figueiredo
Mathematical optimization is deeply pervasive in the vast majority of graphical applications. To study all available methodologies would be the work of a lifetime, however, there is a 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.
This authoritative reference is a consolidated guide to the seminal techniques of mathematical optimization as applied to computer graphics and vision.
It provides a conceptual overview of the key problems in computer graphics and explains the core mathematical models that can be used to solve them, demonstrating their pivotal importance.
It aids readers in finding the right optimization technique for a specific application by providing combinatorial, continuous, variational, and global optimization methods for applications including:
Camera Calibration
Color Correction
Geometric Modeling
Animation
Visualization
Coding and Compression
Image Processing
Computer Vision
Image and Color Quantization
Level of Detail Computation
Interactive Visualization
Minimum Paths in Maps
Surface Reconstruction from Sections
Algorithms, such as Newton methods, linear programming, conjugate gradient and sequential quadratic programming, Dijkstra, and Branch-and-bound, are explained alongside strategies for devising good algorithms. Special emphasis is given to the subtle relationships between probability theory and mathematical optimization. Cutting-edge research is discussed in a section at the end of every chapter, accompanied by targeted references to further reading.
Professionals exploring computer vision, geometric modeling, visualization, animation, and image processing will all benefit from the insights of the authors, who are renowned researchers from IMPA, the Brazilian National Institute for Pure, and Applied Mathematics.
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