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MPI-INF D4 Publications :: Thesis :: Mewes, Daniel

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Thesis - Master's thesis | @MastersThesis | Masterarbeit

Author(s)*:Mewes, Daniel
BibTeX citekey*:MewesThesis2013

Title, School
Title*:Semantic Structuring of Shapes and other Visual Data
School:Universität des Saarlandes
Type of Thesis*:Master's thesis

Note, Abstract, Copyright
LaTeX Abstract:Crowd-sourced data bases such as Flickr for images or Google 3D Warehouse for 3D meshes provide vast amounts of shape data. While the shapes in these databases come annotated with user-provided semantic labels, those annotations are noisy and inconsistent. Organizing these data sets by semantic criteria therefore remains a difficult task. We explore techniques that use machine learning for finding out how images and 3D meshes can be associated with the corresponding semantic labels. We present how an existing method for large-scale image annotation ("WSABIE" by Weston et al. 2011) can be extended to support a multi modal setting, in which we can learn a joint semantic structuring of both meshes and images.
Download Access Level:Internal

Referees, Status, Dates
1. Referee:Hans-Peter Seidel
2. Referee:Michael Wand
Supervisor:Michael Wand
Date Kolloquium:- - -

MPG Unit:Max-Planck-Institut für Informatik
MPG Subunit:Computer Graphics Group
MPG Subsubunit:Statistical Geometry Processing
Audience:experts only
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BibTeX Entry:

AUTHOR = {Mewes, Daniel},
TITLE = {Semantic Structuring of Shapes and other Visual Data},
SCHOOL = {Universit{\"a}t des Saarlandes},
YEAR = {2013},
TYPE = {Master's thesis}
MONTH = {August},

Entry last modified by Daniel Mewes, 01/30/2014
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08/27/2013 11:41:02 AM

Daniel Mewes

Edit Date
08/27/2013 11:41:04 AM