Deformable object animation using reduced optimal control

Barbič, Jernej; Silva, Marco J. da; Popović, Jovan

doi:10.1145/1531326.1531359

Cited by 77 publications

(79 citation statements)

References 39 publications

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“…Many of these methods can be expensive because the optimization scales sharply with the size of the grid, making them impractical for interesting domains. A low dimensional basis offers a good setting to implement control policies that would be intractable in higher dimensions as demonstrated for example by Barbič et al [Barbič et al 2009]. Our method's availability of closed form expressions for time derivatives could also prove useful in optimization algorithms.…”

Section: Future Workmentioning

confidence: 96%

Fluid simulation using Laplacian eigenfunctions

2012

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We present an algorithm for the simulation of incompressible fluid phenomena that is computationally efficient and leads to visually convincing simulations with far fewer degrees of freedom than existing approaches. Rather than using an Eulerian grid or Lagrangian elements, we represent vorticity and velocity using a basis of global functions defined over the entire simulation domain. We show that choosing Laplacian eigenfunctions for this basis provides benefits, including correspondence with spatial scales of vorticity and precise energy control at each scale. We perform Galerkin projection of the Navier-Stokes equations to derive a time evolution equation in the space of basis coefficients. Our method admits closed form solutions on simple domains but can also be implemented efficiently on arbitrary meshes.

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Section: Future Workmentioning

confidence: 96%

Fluid simulation using Laplacian eigenfunctions

2012

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“…Several techniques for simulation of dynamic effects offer such controls, including rigid body [Popović et al 2000], crowd formation [Kwon et al 2008], and deformable objects [Barbič et al 2009]. However, none of the existing methods can handle large scale controls and small scale details simultaneously.…”

Section: Controllable Animation Synthesismentioning

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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“…Because the model normally undergoes dynamic motion, we must employ some mechanism to quickly stabilize the motion to a limit equilibrium configuration. One approach is to perform a Newton-Raphson iteration to seek the model equilibrium under the IK linear spring forces (a static solver [Mezger et al 2008;Barbič et al 2009]). However, such a solver often suffers from a high linear system condition number, which has lead to instabilities in our experiments.…”

Section: Interactive Plant Designmentioning

confidence: 99%

Interactive authoring of simulation-ready plants

Zhao

Barbič

2013

ACM Trans. Graph.

Self Cite

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Figure 1: Simulation of a peach tree with anatomically realistic geometry (Prunus Persica), with fracture. Peaches fall from the tree swaying in the space-time Perlin wind. 299,707 triangles, 237 branches, 3,556 twigs, 18,536 leaves, 330 fruits, 2,950 reduced DOFs, 7 hierarchy levels, 5 msec of simulation per graphical frame. AbstractPhysically based simulation can produce quality motion of plants, but requires an authoring stage to convert plant "polygon soup" triangle meshes to a format suitable for physically based simulation. We give a system that can author complex simulation-ready plants in a manner of minutes. Our system decomposes the plant geometry, establishes a hierarchy, builds and connects simulation meshes, and detects instances. It scales to anatomically realistic geometry of adult plants, is robust to non-manifold input geometry, gaps between branches or leaves, free-flying leaves not connected to any branch, spurious geometry, and plant self-collisions in the input configuration. We demonstrate the results using a FEM model reduction simulator that can compute large-deformation dynamics of complex plants at interactive rates, subject to user forces, gravity or randomized wind. We also provide plant fracture (with prespecified patterns), inverse kinematics to easily pose plants, as well as interactive design of plant material properties. We authored and simulated over 100 plants from diverse climates and geographic regions, including broadleaf (deciduous) trees and conifers, bushes and flowers. Our largest simulations involve anatomically realistic adult trees with hundreds of branches and over 100,000 leaves.

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Deformable object animation using reduced optimal control

Cited by 77 publications

References 39 publications

Fluid simulation using Laplacian eigenfunctions

Fluid simulation using Laplacian eigenfunctions

Dynamic element textures

Interactive authoring of simulation-ready plants

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