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  Structure-aware Content Creation

Wu, X. (2017). Structure-aware Content Creation. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-26697.

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Genre: Thesis
Subtitle : Detection, Retargeting and Deformation

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OA-Status:
Green
Locator:
http://scidok.sulb.uni-saarland.de/doku/lic_ohne_pod.php?la=de (Copyright transfer agreement)
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 Creators:
Wu, Xiaokun1, 2, Author           
Seidel, Hans-Peter1, Advisor                 
Wand, Michael1, Referee           
Hildebrandt, Klaus1, Referee           
Klein, Reinhard3, Referee
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, Campus E1 4, 66123 Saarbrücken, DE, ou_1116551              
3External Organizations, ou_persistent22              

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 Abstract: Nowadays, access to digital information has become ubiquitous, while three-dimensional visual representation is becoming indispensable to knowledge understanding and information retrieval. Three-dimensional digitization plays a natural role in bridging connections between the real and virtual world, which prompt the huge demand for massive three-dimensional digital content. But reducing the effort required for three-dimensional modeling has been a practical problem, and long standing challenge in compute graphics and related fields.
In this thesis, we propose several techniques for lightening up the content creation process, which have the common theme of being structure-aware, \ie maintaining global relations among the parts of shape. We are especially interested in formulating our algorithms such that they make use of symmetry structures, because of their concise yet highly abstract principles are universally applicable to most regular patterns.
We introduce our work from three different aspects in this thesis. First, we characterized spaces of symmetry preserving deformations, and developed a method to explore this space in real-time, which significantly simplified the generation of symmetry preserving shape variants. Second, we empirically studied three-dimensional offset statistics, and developed a fully automatic retargeting application, which is based on verified sparsity. Finally, we made step forward in solving the approximate three-dimensional partial symmetry detection problem, using a novel co-occurrence analysis method, which could serve as the foundation to high-level applications.

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Language(s): eng - English
 Dates: 2016-08-252017-01-202017-01-212017
 Publication Status: Issued
 Pages: viii, 61 p.
 Publishing info: Saarbrücken : Universität des Saarlandes
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: wuphd2017
URN: urn:nbn:de:bsz:291-scidok-67750
DOI: 10.22028/D291-26697
Other: hdl:20.500.11880/26753
 Degree: PhD

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