Turbulence Estimation in Smoke Simulation via Curvature-Based Image Features

Abstract

Smoke simulation is a crucial element in entertainment applications, such as movies and video games. In particular, the required smoke texture varies depending on the scene, ranging from smooth textures for cigarette smoke to highly irregular ones for explosions. The texture of smoke is primarily influenced by light sources, scattering properties, and turbulence components. Light sources and scattering properties affect the appearance of smoke during rendering, influencing its color, brightness, and density. Turbulence components significantly influence the shape of smoke. While many methods have been proposed for generating turbulence components, they all require manual adjustment of turbulence parameters, which is both time-consuming and labor-intensive. To address this issue, we propose a method for easily generating the desired turbulence by estimating turbulence parameters from images. In our approach, users input images including the desired turbulence components, and optimal parameters representing those components are automatically estimated. This reduces the time and effort required for parameter adjustment, allowing the desired turbulence components to be represented more efficiently.