Regularized Optimization Methods for Reconstruction and Modeling in Computer Graphics : Dissertation

Language: English

Published by Bod - Books On Demand, 2014

3735742998 / 9783735742995

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nach der Bestellung gedruckt Neuware - Printed after ordering - The field of computer graphics deals with virtual representations of the real world. These can be obtained either through reconstruction of a model from measurements, or by directly modeling a virtual object, often on a real-world example. The former is often formalized as a regularized optimization problem, in which a data term ensures consistency between model and data and a regularization term promotes solutions that have high a priori probability.In this dissertation, different reconstruction problems in computer graphics are shown to be instances of a common class of optimization problems which can be solved using a uniform algorithmic framework. Moreover, it is shown that similar optimization methods can also be used to solve data-based modeling problems, where the amount of information that can be obtained from measurements is insufficient for accurate reconstruction.As real-world examples of reconstruction problems, sparsity and group sparsity methods are presented for radio interferometric image reconstruction in static and time-dependent settings. As a modeling example, analogous approaches are investigated to automatically create volumetric models of astronomical nebulae from single images based on symmetry assumptions.…

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Title
Regularized Optimization Methods for Reconstruction and Modeling in Computer Graphics : Dissertation
Author
Stephan Wenger
Publisher
Bod - Books On Demand
Publication year
2014
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3735742998
ISBN 13
9783735742995
Item weight
292 grams
Dimensions
210x148x13 mm

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