A unified smoke control method based on signed distance field

Yang, Ben; Liu, Youquan; You, Lihua; Jin, Xiaogang

doi:10.1016/j.cag.2013.05.001

Cited by 12 publications

(15 citation statements)

References 20 publications

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“…The proposed driving force is similar to but different from the control forces, including the boundary control force and the shape control force, presented by Yang et al. 42 The gradients of the sign distance field is employed to estimate the boundary control force. The shape control force is based on the medial axis point clouds, which are extracted using the Laplacian criteria after computing the SDF of the target shape.…”

Section: Direction Of Driving Forcementioning

confidence: 99%

Target‐driven cloud evolution using position‐based fluids

Zhang

Yang

et al. 2020

Computer Animation & Virtual

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To effectively control particle-based cloud evolution without imposing strict position constraints, we propose a novel method integrating a control force field and a phase transition control into the position-based fluids (PBF) framework. To produce realistic cloud simulation, we incorporate both fluid dynamics and thermodynamics to govern cloud particle movement. The fluid dynamics is simulated through our novel driving and damping force terms. As these terms are only formulated based on cloud particle density and position, they simplify the inputs and make our method free from artificial positional constraints. The thermodynamics is implemented by our phase transition control, which can effectively simulate cloud evolution between discrepant initial and target shapes, producing plausible results. Uniquely, our method can also support target shape change during cloud simulation. Experiment results have demonstrated our method surpasses existing methods.

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Section: Direction Of Driving Forcementioning

confidence: 99%

Target‐driven cloud evolution using position‐based fluids

Zhang

Yang

et al. 2020

Computer Animation & Virtual

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“…These meshes can also define specific key-frames to control an animation [Treuille et al 2003;McNamara et al 2004]. Fluid trajectories, on their sides, may be controlled with user-defined velocity fields [Kim et al 2006], distance fields [Yang et al 2013], or specific control particles [Thürey et al 2006;Madill and Mould 2013].…”

Section: Fluid Simulation Controlmentioning

confidence: 99%

Space-time sculpting of liquid animation

Manteaux

Vimont

Wojtan

et al. 2016

Proceedings of the 9th International Conference on Motion in Games

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International audienceWe propose an interactive sculpting system for seamlessly editing pre-computed animations of liquid, without the need for any re-simulation. The input is a sequence of meshes without correspondences representing the liquid surface over time. Our method enables the efficient selection of consistent space-time parts of this animation, such as moving waves or droplets, which we call space-time features. Once selected, a feature can be copied, edited, or duplicated and then pasted back anywhere in space and time in the same or in another liquid animation sequence. Our method circumvents tedious user interactions by automatically computing the spatial and temporal ranges of the selected feature. We also provide space-time shape editing tools for non-uniform scaling, rotation, trajectory changes, and temporal editing to locally speed up or slow down motion. Using our tools, the user can edit and progressively refine any input simulation result, possibly using a library of pre-computed space-time features extracted from other animations. In contrast to the trial-and-error loop usually required to edit animation results through the tuning of indirect simulation parameters, our method gives the user full control over the edited space-time behaviors

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“…Beside shape control, Kim et al proposed a smoke path control algorithm by using linear feedback control. Yang et al proposed a unified smoke animation control algorithm based on signed distance field. It can deal with both path control and shape control satisfactorily in the same framework.…”

Section: Related Workmentioning

confidence: 99%

“…We use the Modified MacCormack algorithm to advect velocity and density. For the control forces, we employ the algorithm by Yang et al . For more details about solving the equations, please refer to and .…”

Section: Algorithmmentioning

confidence: 99%

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Turbulence synthesis for shape‐controllable smoke animation

Yang

Jin

2014

Computer Animation & Virtual

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We present a novel procedural synthesis method to improve small-scale turbulence details for controllable smoke animation constrained by shapes and paths. In order to enhance fluid details without introducing unpleasing fluid control effects, we propose a spatial-temporal varying synthesis parameter to control turbulence behaviors and compute it from control force and the vorticity velocity. Our approach can control enhanced turbulence behaviors efficiently and produces visually plausible realistic fine-scale details while reducing artifacts of large-scale noises on fluid control. We compare our algorithm to existing procedural synthesis ones to validate its efficiency and controllability.

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A unified smoke control method based on signed distance field

Cited by 12 publications

References 20 publications

Target‐driven cloud evolution using position‐based fluids

Target‐driven cloud evolution using position‐based fluids

Space-time sculpting of liquid animation

Turbulence synthesis for shape‐controllable smoke animation

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