Piles of objects

Hsu, Shu-Wei; Keyser, John

doi:10.1145/1882261.1866181

Cited by 11 publications

(6 citation statements)

References 19 publications

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“…As discussed in [Cho et al 2007], physically implausible configurations are often desired in real production scenarios. Figure 13 demonstrates potential cases which cannot be produced by physical simulation (not stable) even with the assistance of frozen elements during piling [Hsu and Keyser 2010]. We have also found such complex elements very difficult to synthesize well with only one sample per element as in our basic algorithm (see Figure 14) and prior data-driven element synthesis methods which, to our knowledge, predominantly use a single sample per element.…”

Section: Output Domain Propertiesmentioning

confidence: 94%

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Discrete element textures

2011

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a) plum stack (b) pebble sculpture (c) dish of corn kernels, carrots, beans (d) spaghetti Figure 1: Discrete element textures. Given a small input exemplar (left within each image), our method synthesizes a corresponding output with user specifiedcoarse-scale domain (right within each image). Using a data driven approach, we can achieve a variety of effects, including (a) regular distribution, (b) output with different domain shape and boundary conditions from the input, (c) mixture of different elements, and (d) deformable and elongated shapes. AbstractA variety of phenomena can be characterized by repetitive small scale elements within a large scale domain. Examples include a stack of fresh produce, a plate of spaghetti, or a mosaic pattern.Although certain results can be produced via manual placement or procedural/physical simulation, these methods can be labor intensive, difficult to control, or limited to specific phenomena.We present discrete element textures, a data-driven method for synthesizing repetitive elements according to a small input exemplar and a large output domain. Our method preserves both individual element properties and their aggregate distributions. It is also general and applicable to a variety of phenomena, including different dimensionalities, different element properties and distributions, and different effects including both artistic and physically realistic ones. We represent each element by one or multiple samples whose positions encode relevant element attributes including position, size, shape, and orientation. We propose a sample-based neighborhood similarity metric and an energy optimization solver to synthesize desired outputs that observe not only input exemplars and output domains but also optional constraints such as physics, orientation fields, and boundary conditions. As a further benefit, our method can also be applied for editing existing element distributions.

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Section: Output Domain Propertiesmentioning

confidence: 94%

“…On one hand this provides the flexibility for the users to choose whatever shapes they like, but on the other hand it may be a nuisance if the users do not feel like doing so. For the latter case it would be interesting to apply more automatic methods to determine the output shape [Hsu and Keyser 2010].…”

Section: Limitations and Future Workmentioning

confidence: 99%

Discrete element textures

2011

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“…al . [BYM05] animated granular materials using discrete elements, while Hsu and Keyser [HK10] substituted piles of interacting objects with static “sleeping” bodies, in order to significantly speed up simulation time. Follow‐up work by Han et.…”

Section: Related Workmentioning

confidence: 99%

A Practical Method for Animating Anisotropic Elastoplastic Materials

Schreck

Wojtan

2020

Computer Graphics Forum

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This paper introduces a simple method for simulating highly anisotropic elastoplastic material behaviors like the dissolution of fibrous phenomena (splintering wood, shredding bales of hay) and materials composed of large numbers of irregularly‐shaped bodies (piles of twigs, pencils, or cards). We introduce a simple transformation of the anisotropic problem into an equivalent isotropic one, and we solve this new “fictitious” isotropic problem using an existing simulator based on the material point method. Our approach results in minimal changes to existing simulators, and it allows us to re‐use popular isotropic plasticity models like the Drucker‐Prager yield criterion instead of inventing new anisotropic plasticity models for every phenomenon we wish to simulate.

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“…General multi-body simulations [HK10] Procedural techniques rely on simple production rules to generate distributions of objects organized into patterns or structures. General multi-body simulations [HK10] Procedural techniques rely on simple production rules to generate distributions of objects organized into patterns or structures.…”

Section: Related Workmentioning

confidence: 99%

Efficient modeling of entangled details for natural scenes

Guérin

Galin

Grosbellet

et al. 2016

Computer Graphics Forum

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Input objectsGhost Tile Rocks field Grass field Branches field Figure 1: Our method allows for the automatic generation of ground details such as grass tufts, rock piles, fallen leaves or twigs in natural landscapes. Given a set of geometric models, our algorithm automatically creates a Ghost Tile structure that stores overlapping candidate objects and a graph representing collisions between them. Given user-defined control density fields, our method instantiates candidates according to collision constraints stored in the graph. This control enables us to sculpt complex piles and thick layers of entangled objects. AbstractDigital landscape realism often comes from the multitude of details that are hard to model such as fallen leaves, rock piles or entangled fallen branches. In this article, we present a method for augmenting natural scenes with a huge amount of details such as grass tufts, stones, leaves or twigs. Our approach takes advantage of the observation that those details can be approximated by replications of a few similar objects and therefore relies on mass-instancing. We propose an original structure, the Ghost Tile, that stores a huge number of overlapping candidate objects in a tile, along with a pre-computed collision graph. Details are created by traversing the scene with the Ghost Tile and generating instances according to user-defined density fields that allow to sculpt layers and piles of entangled objects while providing control over their density and distribution.

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Piles of objects

Cited by 11 publications

References 19 publications

Discrete element textures

Discrete element textures

A Practical Method for Animating Anisotropic Elastoplastic Materials

Efficient modeling of entangled details for natural scenes

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