Modeling and estimation of energy-based hyperelastic objects Journal Article


Author(s): Miguel, Eder; Miraut, David; Otaduy, Miguel A
Article Title: Modeling and estimation of energy-based hyperelastic objects
Affiliation IST Austria
Abstract: In this paper, we present a method to model hyperelasticity that is well suited for representing the nonlinearity of real-world objects, as well as for estimating it from deformation examples. Previous approaches suffer several limitations, such as lack of integrability of elastic forces, failure to enforce energy convexity, lack of robustness of parameter estimation, or difficulty to model cross-modal effects. Our method avoids these problems by relying on a general energy-based definition of elastic properties. The accuracy of the resulting elastic model is maximized by defining an additive model of separable energy terms, which allow progressive parameter estimation. In addition, our method supports efficient modeling of extreme nonlinearities thanks to energy-limiting constraints. We combine our energy-based model with an optimization method to estimate model parameters from force-deformation examples, and we show successful modeling of diverse deformable objects, including cloth, human finger skin, and internal human anatomy in a medical imaging application.
Keywords: deformation; Parameter estimation; Medical imaging; Elasticity; Deformable object; Elastic modeling; Elastic properties; Energy-based models; Force deformation; Imaging applications; Optimization method; Real-world objects
Journal Title: Computer Graphics Forum
Volume: 35
Issue 2
ISSN: 1467-8659
Publisher: Wiley  
Date Published: 2016-05-01
Start Page: 385
End Page: 396
DOI: 10.1111/cgf.12840
Notes: We wish to thank the anonymous reviewers for their helpful com- ments. We also thank Taehyun Rhee for the knee data; Derek Bradley for help with the cloth data; Maria Laura D’Angelo, Mat- teo Bianchi and Ferdinando Cannella for the finger data; and Rosell Torres and José Miguel Espadero for help with the volume raster- ization software. This work was funded in part by grants from the Spanish Ministry of Economy (TIN2012-35840), the European Re- search Council (ERC Starting Grant no. 280135 Animetrics), and the EU FP7 (project no. 601165 WEARHAP).
Open access: no
IST Austria Authors
  1. Eder Miguel
    5 Miguel
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