<Title>Data-Driven Estimation of Cloth Simulation Models</Title>
      
      
        
          E. Miguel
          1
          2
        
        
          D. Bradley 2 B. Thomaszewski 2 B. Bickel 2 W. Matusik
          2
        
        
          M. A. Otaduy 1 S. Marschner
        
      
      1. URJC Madrid 2. Disney Research Zurich
      
        
        Figure 1: We capture deformation behaviors of cloth materials with a dedicated setup (column 1 from left). The measurement images (2) are reconstructed into 3D geometry (3) yielding dense deformation fields. We use this data to fit parameters and investigate approximation qualities of three common cloth models: springs (4), soft constraints (5), and the StVK model (6).
      
      <Abstract>Progress in cloth simulation for computer animation and apparel design has led to a multitude of deformation models, each with its own way of relating geometry, deformation, and forces. As simulators improve, differences between these models become more important, but it is difficult to choose a model and a set of parameters to match a given real material simply by looking at simulation results. This paper provides measurement and fitting methods that allow nonlinear models to be fit to the observed deformation of a particular cloth sample. Unlike standard textile testing, our system measures complex 3D deformations of a sheet of cloth, not just one-dimensional force–displacement curves, so it works under a wider range of deformation conditions. The fitted models are then evaluated by comparison to measured deformations with motions very different from those used for fitting.</Abstract>
    
    
      
        