Data-driven elastic models for cloth

Wang, Huamin; O’Brien, James F.; Ramamoorthi, Ravi

doi:10.1145/1964921.1964966

Cited by 117 publications

(149 citation statements)

References 31 publications

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“…We used the sparse Cholesky-based solver in the TAUCS library for solving the linear systems arising from implicit time integration and Newton's method. The constitutive model used for the T-shirt was the "Gray Interlock" material measured from real fabric by Wang et al [2011].…”

Section: Resultsmentioning

confidence: 99%

Folding and crumpling adaptive sheets

2013

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Figure 1: Crumpling a sheet of paper is a challenging process to simulate as it produces geometry with both sharp creases and smooth areas. We efficiently resolve the emerging detail in the material through adaptive remeshing. AbstractWe present a technique for simulating plastic deformation in sheets of thin materials, such as crumpled paper, dented metal, and wrinkled cloth. Our simulation uses a framework of adaptive mesh refinement to dynamically align mesh edges with folds and creases. This framework allows efficient modeling of sharp features and avoids bend locking that would be otherwise caused by stiff in-plane behavior. By using an explicit plastic embedding space we prevent remeshing from causing shape diffusion. We include several examples demonstrating that the resulting method realistically simulates the behavior of thin sheets as they fold and crumple.

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Section: Resultsmentioning

confidence: 99%

Folding and crumpling adaptive sheets

2013

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“…However, these models are often hard to parametrize and are tailored towards specific materials and loading scenarios. An investigation of datadriven methods to capture plastic and fracture behavior, as has been done for elastic parameters of cloth [Wang et al 2011], would be an interesting avenue for future work.…”

Section: Discussionmentioning

confidence: 99%

Adaptive tearing and cracking of thin sheets

et al. 2014

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Figure 1: Our method produces realistic tearing and cracking phenomena for thin sheets made from a wide variety of materials such as cork, foil, plastic, metal, or vinyl. These results are achieved using simulation on adaptive meshes that resolve fracture behavior at very high resolution. AbstractThis paper presents a method for adaptive fracture propagation in thin sheets. A high-quality triangle mesh is dynamically restructured to adaptively maintain detail wherever it is required by the simulation. These requirements include refining where cracks are likely to either start or advance. Refinement ensures that the stress distribution around the crack tip is well resolved, which is vital for creating highly detailed, realistic crack paths. The dynamic meshing framework allows subsequent coarsening once areas are no longer likely to produce cracking. This coarsening allows efficient simulation by reducing the total number of active nodes and by preventing the formation of thin slivers around the crack path. A local reprojection scheme and a substepping fracture process help to ensure stability and prevent a loss of plasticity during remeshing. By including bending and stretching plasticity models, the method is able to simulate a large range of materials with very different fracture behaviors.

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“…These elements need multiple samples per element to accurately characterize geometries and motions both within and across elements, including the 2D topological constraints. Adding dynamic details for sheets via data driven synthesis has recently attracted a lot of attention [Wang et al 2011;Kavan et al 2011]. However, most of these methods aim to reproduce physical realism with more efficient computations.…”

Section: Sheetsmentioning

confidence: 99%

Dynamic element textures

Wei

Lefèbvre

et al. 2013

ACM Trans. Graph.

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(a) particles (b) herds (c) threads (d) sheets Figure 1: Dynamic element textures. Our method synthesizes a variety of repetitive spatial-temporal phenomena, such as particles, threads, and sheets, via a combination of constrained optimization and data driven computation. It offers control at both the coarse scale through spatial-temporal constraints (e.g. overall output shape and movement) and the fine scale through small input exemplars (bottom-left inlet of each image), which may be static (a) or animated (b), (c) and (d). Please refer to the accompanying video for corresponding animations of our results. AbstractMany natural phenomena consist of geometric elements with dynamic motions characterized by small scale repetitions over large scale structures, such as particles, herds, threads, and sheets. Due to their ubiquity, controlling the appearance and behavior of such phenomena is important for a variety of graphics applications. However, such control is often challenging; the repetitive elements are often too numerous for manual edit, while their overall structures are often too versatile for fully automatic computation.We propose a method that facilitates easy and intuitive controls at both scales: high-level structures through spatial-temporal output constraints (e.g. overall shape and motion of the output domain), and low-level details through small input exemplars (e.g. element arrangements and movements). These controls are suitable for manual specification, while the corresponding geometric and dynamic repetitions are suitable for automatic computation. Our system takes such user controls as inputs, and generates as outputs the corresponding repetitions satisfying the controls.Our method, which we call dynamic element textures, aims to produce such controllable repetitions through a combination of constrained optimization (satisfying controls) and data driven computation (synthesizing details). We use spatial-temporal samples as the core representation for dynamic geometric elements. We propose analysis algorithms for decomposing small scale repetitions from large scale themes, as well as synthesis algorithms for generating outputs satisfying user controls. Our method is general, producing a range of artistic effects that previously required disparate and specialized techniques.

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Data-driven elastic models for cloth

Cited by 117 publications

References 31 publications

Folding and crumpling adaptive sheets

Folding and crumpling adaptive sheets

Adaptive tearing and cracking of thin sheets

Dynamic element textures

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