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          Institute: MPI für Informatik     Collection: Computer Graphics Group     Display Documents



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ID: 278961.0, MPI für Informatik / Computer Graphics Group
Feature Sensitive Mesh Segmentation with Mean Shift
Authors:Yamauchi, Hitoshi; Lee, Seungyong; Lee, Yunjin; Ohtake, Yutaka; Belyaev, Alexander; Seidel, Hans-Peter
Editors:Spagnuolo, Michaela; Pasko, Alexander; Belyaev, Alexander
Language:English
Publisher:IEEE
Place of Publication:Los Alamitos, USA
Date of Publication (YYYY-MM-DD):2005
Title of Proceedings:Shape Modeling International 2005 (SMI 2005)
Start Page:236
End Page:243
Place of Conference/Meeting:Cambridge, MA, USA
(Start) Date of Conference/Meeting
 (YYYY-MM-DD):
2005-06-15
Review Status:not specified
Audience:Experts Only
Intended Educational Use:No
Abstract / Description:Feature sensitive mesh segmentation is important for many
computer graphics and geometric modeling applications. In this
paper, we develop a mesh segmentation method which is capable of
producing high-quality shape partitioning. It respects fine shape
features and works well on various types of shapes, including
natural shapes and mechanical parts.
The method combines a procedure for clustering mesh normals
with a modification of the mesh chartification technique \cite{Sander_sig03}.
For clustering of mesh normals, we adapt Mean Shift,
a powerful general purpose technique for clustering scattered data.
We demonstrate advantages of our method by comparing it with two
state-of-the-art mesh segmentation techniques.
Last Change of the Resource (YYYY-MM-DD):2006-04-25
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Hans-Peter Seidel
Affiliations:MPI für Informatik/Computer Graphics Group
Identifiers:ISBN:0-7695-2379-X
LOCALID:C125675300671F7B-40645AA425C269E4C1256FC60056CA4F-...
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