research-article

Randomized cuts for 3D mesh analysis

Authors:

Aleksey Golovinskiy,

Thomas FunkhouserAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 27, Issue 5

Article No.: 145, Pages 1 - 12

https://doi.org/10.1145/1409060.1409098

Published: 01 December 2008 Publication History

Abstract

The goal of this paper is to investigate a new shape analysis method based on randomized cuts of 3D surface meshes. The general strategy is to generate a random set of mesh segmentations and then to measure how often each edge of the mesh lies on a segmentation boundary in the randomized set. The resulting "partition function" defined on edges provides a continuous measure of where natural part boundaries occur in a mesh, and the set of "most consistent cuts" provides a stable list of global shape features. The paper describes methods for generating random distributions of mesh segmentations, studies sensitivity of the resulting partition functions to noise, tessellation, pose, and intra-class shape variations, and investigates applications in mesh visualization, segmentation, deformation, and registration.

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Index Terms

Randomized cuts for 3D mesh analysis
1. Computing methodologies
  1. Computer graphics
    1. Shape modeling
      1. Parametric curve and surface models
      2. Volumetric models
2. Theory of computation
  1. Models of computation
    1. Probabilistic computation
  2. Randomness, geometry and discrete structures

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 27, Issue 5

December 2008

552 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1409060

Issue’s Table of Contents

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 December 2008

Published in TOG Volume 27, Issue 5

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Cited By

Zhang RPan SLv CGong MHuang H(2024)Architectural Co-LOD GenerationACM Transactions on Graphics10.1145/368790543:6(1-16)Online publication date: 19-Dec-2024
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R RA AS AM N(2024)Zooviz – Unveiling Anatomy Virtually2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)10.1109/ICPECTS62210.2024.10780123(1-5)Online publication date: 8-Oct-2024
https://doi.org/10.1109/ICPECTS62210.2024.10780123
Guo AZhang ZGao FDu HLiu XLi B(2023)Applications of Convolutional Neural Networks to Extracting Oracle Bone Inscriptions from Three-Dimensional ModelsSymmetry10.3390/sym1508157515:8(1575)Online publication date: 12-Aug-2023
https://doi.org/10.3390/sym15081575
Kim JMo KSung MWoo W(2023)Seg&Struct: The Interplay Between Part Segmentation and Structure Inference for 3D Shape Parsing2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV56688.2023.00128(1226-1235)Online publication date: Jan-2023
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Lin WHuang Q(2023)Automated deviation-aware landmark selection for freeform product accuracy qualification in 3D printingIISE Transactions10.1080/24725854.2023.228060656:12(1321-1330)Online publication date: 20-Dec-2023
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Mu ALiu ZDuan GTan J(2023)Part-to-Surface Mesh Segmentation for Mechanical Models Based on Multi-Stage ClusteringComputer-Aided Design10.1016/j.cad.2023.103545162:COnline publication date: 1-Sep-2023
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Asgharian LEbrahimnezhad H(2023)3D model representation using space curves: an efficient mesh simplification method by exchanging triangulated mesh to space curvesMultimedia Tools and Applications10.1007/s11042-023-14777-482:20(30965-31000)Online publication date: 22-Feb-2023
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