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Summary: Smoothing 3D Meshes
using Markov Random Fields
Master's thesis
Vedrana Andersen
vedrana@itu.dk
130274-xxxx
Supervisors:
Mads Nielsen, Professor, DIKU
Henrik Aanęs, Associate Professor, DTU
ITU, September 2006 - April 2007
2
Abstract
This thesis investigates the use of Markov Random Fields (MRF) for formulating
priors on 3D surfaces represented as triangle meshes. The problem is addressed
by focusing on mesh smoothing, which is of great interest in many applications of
geometry processing, e.g., computer vision and reverse engineering.
Firstly, a mesh-smoothing vertex process is developed. It is a process that
combines a smoothness prior described through MRF with the simple observa-
tion model into MAP-MRF framework. An edge process for detecting features
(ridges) is developed next, where the feature-detecting function allows specifying
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