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Cited by 813D Shape Modeling and AnalysisComputer Graphics and Visualization TechniquesComputational Geometry and Mesh Generation

Reconstructing Animated Meshes from Time‐Varying Point Clouds

Süßmuth, Jochen, Winter, Marco, Greiner, Günther·2008·Computer Graphics Forum
DOI 10.1111/j.1467-8659.2008.01287.x
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Abstract

In this paper, we describe a novel approach for the reconstruction of animated meshes from a series of time‐deforming point clouds. Given a set of unordered point clouds that have been captured by a fast 3‐D scanner, our algorithm is able to compute coherent meshes which approximate the input data at arbitrary time instances. Our method is based on the computation of an implicit function in ℝ 4 that approximates the time‐space surface of the time‐varying point cloud. We then use the four‐dimensional implicit function to reconstruct a polygonal model for the first time‐step. By sliding this template mesh along the time‐space surface in an as‐rigid‐as‐possible manner, we obtain reconstructions for further time‐steps which have the same connectivity as the previously extracted mesh while recovering rigid motion exactly. The resulting animated meshes allow accurate motion tracking of arbitrary points and are well suited for animation compression. We demonstrate the qualities of the proposed method by applying it to several data sets acquired by real‐time 3‐D scanners.

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  • Although many non-rigid deformation models are different in formulation, they all have one common characteristic: they all try to preserve some kind of smoothness.

    “Although many of these non-rigid deformation models are different in terms of formulation, they all have one common characteristic.Whether they use adjacency similarity, gradient or Laplacian fields [28] (first-order), thin-plate splines [35] (second-order), or various regularizers (Section 4.2.6), they all try to preserve some kind of smoothness.”

    From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [28]

  • [6], [28], [79] constructs a template, an urshape, by accumulating and filling in missing data from other scans in the same sequence. They have been used extensively in non-rigid registration to constrain dense correspondences. This works for objects with well defined forms, such as the human face and body.

    “[6], [28], [79] constructs a template, an urshape, by accumulating and filling in missing data from other scans in the same sequence.They have been used extensively in non-rigid registration to constrain dense correspondences [23], [29], [32], [34], [80].This works for objects with well defined forms, such as the human face and body.”

    From Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid (2013) · cites this paper as [28]

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Authors
Süßmuth, J., Winter, M., & Greiner, G.
Affiliations
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
ORCID
Venue
Computer Graphics Forum
Publisher
Wiley
Published
2008-07
Volume
27
Issue
5
Pages
1469-1476
ISSN
  • 0167-7055 (ISSN-L)
  • 1467-8659
DOI
10.1111/j.1467-8659.2008.01287.x
OpenAlex
W2028653923
Cited by
81
References
26
Citations by year
2026: 1 · 2025: 1 · 2022: 2 · 2021: 3 · 2020: 1 · 2019: 10 · 2018: 9 · 2017: 5 · 2016: 7 · 2015: 6 · 2014: 5 · 2013: 5 · 2012: 5
FWCI
7.33
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor, 90 d)
Locations
Computer Graphics Forum (publishedVersion)
Topics
  • Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computational Geometry and Mesh Generation
Keywords
implicit functions, as-rigid-as-possible deformation, 3D scanning, motion tracking

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