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Subspace Clothing Simulation Using Adaptive Bases

Fabian Hahn, Bernhard Thomaszewski, Stelian Coros, Robert W. Sumner, Forrester Cole, Mark Meyer, Tony DeRose, Markus Gross

SIGGRAPHDisney Research108 citesCFX

Subspace cloth simulation using pose-dependent adaptive bases, enabling fast and plausible garment simulation for animated characters.

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Abstract

We present a new approach to clothing simulation using low-dimensional linear subspaces with temporally adaptive bases. Our method exploits full-space simulation training data in order to construct a pool of low-dimensional bases distributed across pose space. For this purpose, we interpret the simulation data as offsets from a kinematic deformation model that captures the global shape of clothing due to body pose. During subspace simulation, we select low-dimensional sets of basis vectors according to the current pose of the character and the state of its clothing. Thanks to this adaptive basis selection scheme, our method is able to reproduce diverse and detailed folding patterns with only a few basis vectors. Our experiments demonstrate the feasibility of subspace clothing simulation and indicate its potential in terms of quality and computational efficiency.

How to read this

Category: Method: subspace (reduced-order) clothing simulation with adaptive bases
Contributions: A pose-distributed pool of low-dimensional linear bases built from full-space simulation training data
Interpretation of simulation data as offsets from a kinematic deformation model capturing pose-driven global garment shape
Temporally adaptive basis selection from current pose and cloth state, reproducing detailed folds with few basis vectors
Context: Builds on data-driven reduced clothing work such as 'Stable Spaces for Real-time Clothing', advancing it from a fixed subspace to pose-dependent adaptive bases.Builds on: Stable Spaces for Real-time Clothing
Correctness: Quality depends on coverage of the training poses and on the assumption that garment behavior is well represented as offsets from the kinematic model; the paper frames results as demonstrating feasibility and potential, so generalization beyond trained pose space is a limitation to keep in mind.
Clarity: Readable; a first pass conveys the adaptive-basis idea, a second pass clarifies the basis construction and selection scheme.
How to read it: First pass for the adaptive-basis concept and the offset-from-kinematic-model framing; do a second pass on how bases are distributed across pose space and selected at runtime if reduced-order quality matters to you.

Builds on

Stable Spaces for Real-time Clothing 2010

Built upon by

Nothing yet.

Related work

Efficient Simulation of Example-Based Materials 2012 / SCA
A Pixel-Based Framework for Data-Driven Clothing 2020 / SCA
A Unified Approach for Subspace Simulation of Deformable Bodies in Multiple Domains 2015 / TOG
Progressive Simulation for Cloth Quasistatics 2022 / TOG

Keywords

subspace simulation cloth simulation adaptive basis pose space deformation model reduction linear subspace kinematic deformation pca newton iteration wrinkles folding patterns reduced coordinates implicit euler pose-dependent basis

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