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MPI-INF D4 Publications :: Thesis :: Kerber, Jens


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Thesis - Doctoral dissertation | @PhdThesis | Doktorarbeit


Author
Author(s)*:Kerber, Jens
BibTeX citekey*:Kerber2013_2
Language:English

Title, School
Title*:Of Assembling Small Sculptures and Disassembling Large Geometry
School:Universität des Saarlandes
Type of Thesis*:Doctoral dissertation
Month:September
Year:2013


Note, Abstract, Copyright
LaTeX Abstract:This thesis describes the research results and contributions that have been achieved during the author’s doctoral work. It is divided into two independent parts, each of which is devoted to a particular research aspect.

                        The first part covers the true-to-detail creation of digital pieces of art, so-called
                        relief sculptures, from given 3D models. The main goal is to limit the depth of the
                        contained objects with respect to a certain perspective without compromising the
                        initial three-dimensional impression. Here, the preservation of significant features
                        and especially their sharpness is crucial. Therefore, it is necessary to overemphasize fine surface details to ensure their perceptibility in the more complanate relief.Our developments are aimed at amending the flexibility and user-friendliness during the generation process. The main focus is on providing real-time solutions with intuitive usability that make it possible to create precise, lifelike andaesthetic results. These goals are reached by a GPU implementation, the use of efficient filtering techniques, and the replacement of user defined parameters by adaptive values. Our methods are capable of processing dynamic scenes and allow the generation of seamless artistic reliefs which can be composed of multiple elements.
                        The second part addresses the analysis of repetitive structures, so-called symmetries, within very large data sets. The automatic recognition of components
                        and their patterns is a complex correspondence problem which has numerous applications ranging from information visualization over compression to automatic
                        scene understanding. Recent algorithms reach their limits with a growing amount
                        of data, since their runtimes rise quadratically. Our aim is to make even massive
                        data sets manageable. Therefore, it is necessary to abstract features and to develop a suitable, low-dimensional descriptor which ensures an efficient, robust, and purposive search. A simple inspection of the proximity within the descriptor space helps to significantly reduce the number of necessary pairwise comparisons. Our method scales quasi-linearly and allows a rapid analysis of data sets which could not be handled by prior approaches because of their size.

Keywords:relief generation, symmetry detection, shape processing, computer art, scene analysis
HyperLinks / References / URLs:http://scidok.sulb.uni-saarland.de/frontdoor.php?source_opus=5516&la=de
Download Access Level:Internal

Referees, Status, Dates
1. Referee:Prof. Dr. Hans-Peter Seidel
2. Referee:Prof. Dr. Alexander Belyaev, Dr. Michael Wand
Supervisor:Prof. Dr. Hans-Peter Seidel
Status:Completed
Date Kolloquium:17 September 2013
Chair Kolloquium:Prof. Thorsten Herfet

Correlation
MPG Unit:Max-Planck-Institut für Informatik
MPG Subunit:Computer Graphics Group
Appearance:MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort

BibTeX Entry:
@PHDTHESIS{Kerber2013_2,
AUTHOR = {Kerber, Jens},
TITLE = {Of Assembling Small Sculptures and Disassembling Large Geometry},
SCHOOL = {Universit{\"a}t des Saarlandes},
YEAR = {2013},
TYPE = {Doctoral dissertation}
PAGES = {116},
MONTH = {September},
}



Entry last modified by Marc Schmitt, 01/30/2014
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Editor(s)
[Library]
Created
09/30/2013 02:08:45 PM
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Editor(s)
Marc Schmitt
Ellen Fries
Jens Kerber
Jens Kerber
Edit Dates
15.11.2013 15:18:04
07.10.2013 11:24:56
09/30/2013 02:10:13 PM
09/30/2013 02:08:45 PM