Data‐Driven Estimation of Cloth Simulation Models

TLDR

Advances in cloth simulation have produced many deformation models that relate geometry, deformation, and forces, yet selecting a model and parameters to match real materials remains difficult as differences between models grow with simulator improvements. The study introduces measurement and fitting techniques that enable nonlinear cloth models to be calibrated to the deformation of a specific cloth sample. The authors employ a system that captures full 3D deformations of cloth sheets under diverse conditions, then evaluate the fitted nonlinear models by comparing them to deformations from motions distinct from the fitting data.

Abstract

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.