An Introduction to Optimization Techniques in Computer Graphics
Author(s) -
Ivo Ihrke,
Xavier Granier,
Gaël Guennebaud,
Laurent Jacques,
Bastian Goldlüecke
Publication year - 2014
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2312/egt.20141019
Subject(s) - computer science , stability (learning theory) , computer graphics , set (abstract data type) , convergence (economics) , optimization problem , graphics , range (aeronautics) , outcome (game theory) , mathematical optimization , algorithm , artificial intelligence , machine learning , computer graphics (images) , mathematics , engineering , programming language , mathematical economics , aerospace engineering , economics , economic growth
Background: Many students in Computer Science do not have a sufficient background in applied mathematics to employ state-of-the-art optimization techniques and to judge the outcome of such techniques critically (e.g. regarding the stability/quality/accuracy of their output). At the same time, the use of optimization techniques in computer graphics is becoming ubiquitous. Treating optimization algorithms as a black box yields sub-optimal results at best. At worst, stability issues and convergence problems may prevent the solution of a problem or impede the general application of a method to a wide range of input, i.e. beyond the set of examples shown in a paper. The course will draw attention to these aspects and to current best practices. This will enable participants to judge articles that use optimization schemes critically and improve their own skill set.
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