MATHEMATICAL OPTIMIZATION IN COMPUTER GRAPHICS AND VISION

Mathematical optimization is deeply pervasive in the vast majority of graphical applications. To study every available methodology would be the work of a lifetime, however, there is a core set of techniques that all computer graphics professionals should understand in order to envision and expand the boundaries of what is possible in their work." "Algorithms, such as Newton methods, linear programming, conjugate gradient and sequential quadratic programming, Dijkstra, and Branch-and-bound, are explained alongside strategies for devising original 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.