Interpolations of Smoke and Liquid Simulations

TL;DR

This paper introduces a new method for interpolating smoke and liquid simulations using dense space-time deformation and optical flow techniques, enabling efficient creation of intermediate fluid states with automatic matching and topology handling.

Contribution

The authors develop a novel implicit Eulerian representation and a five-dimensional optical flow approach for robust, automatic interpolation of fluid simulations with topology changes.

Findings

Effective interpolation of swirling smoke clouds

Smooth transitions between liquid and smoke phenomena

Automatic matching without user input

Abstract

We present a novel method to interpolate smoke and liquid simulations in order to perform data-driven fluid simulations. Our approach calculates a dense space-time deformation using grid-based signed-distance functions of the inputs. A key advantage of this implicit Eulerian representation is that it allows us to use powerful techniques from the optical flow area. We employ a five-dimensional optical flow solve. In combination with a projection algorithm, and residual iterations, we achieve a robust matching of the inputs. Once the match is computed, arbitrary in between variants can be created very efficiently. To concatenate multiple long-range deformations, we propose a novel alignment technique. Our approach has numerous advantages, including automatic matches without user input, volumetric deformations that can be applied to details around the surface, and the inherent handling of topology changes. As a result, we can interpolate swirling smoke clouds, and splashing liquid simulations. We can even match and interpolate phenomena with fundamentally different physics: a drop of liquid, and a blob of heavy smoke.