Reclustering for large plasticity in clustered shape matching

Michael Falkenstein, Ben Jones, Joshua A. Levine, Tamar Shinar, Adam W. Bargteil

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


In this paper, we revisit the problem online reclustering in clustered shape matching simulations and propose an approach that employs two nonlinear optimizations to create new clusters. The first optimization finds the embedding of particles and clusters into three-dimensional space that minimizes elastic energy. The second finds the optimal location for the new cluster, working in this embedded space. The result is an approach that is more robust in the presence of elastic deformation. We also experimentally verify that our clustered shape matching approach converges as the number of clusters increases, suggesting that our reclustering approach does not change the underlying material properties. Further, we demonstrate that particle resampling is not strictly necessary in our framework allowing us to trivially conserve volume. Finally, we highlight an error in estimating rotations in the original shape-matching work [Müller et al. 2005] that has been repeated in much of the follow up work.

Original languageEnglish (US)
Title of host publicationProceedings - MIG 2017
Subtitle of host publicationMotion in Games
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450355414
StatePublished - Nov 8 2017
Event10th International Conference on Motion in Games, MIG 2017 - Barcelona, Spain
Duration: Nov 8 2017Nov 10 2017

Publication series

NameProceedings - MIG 2017: Motion in Games


Conference10th International Conference on Motion in Games, MIG 2017


  • Clustering
  • Plasticity
  • Shape Matching

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software
  • Human-Computer Interaction


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