Image Based Whole Sky Cloud Volume Generation

Accurate illumination is crucial for many imaging and vision applications, and skies are the dominant source of lighting in many scenes. Most existing work for representing sky illumination has focused on clear skies or more recently generative approaches for synthesizing clouds. However, these are very limited in that they assume distant illumination and do not capture the 3D properties of clouds. This paper presents a novel and principled approach to extract 3D whole-sky volumetric representations of clouds which can be used for imaging applications. Our approach extracts clouds from a single fisheye capture of the sky via an iterative optimization process. We achieve this by exploiting the physical properties of light scattering in clouds and use these to drive a domain-specific light transport simulation algorithm to render the images required for optimization. Results for this method provide high accuracy when re-rendering with our reconstructed clouds compared to real captures, and also enable novel uses of environment maps such as inclusion of captured clouds in renderings, cloud shadows, and more accurate aerial perspective and lighting.