Stroke Transfer for Participating Media

We present a method for generating stroke-based painterly drawings of participating media, such as smoke, fire, and clouds, by transferring stroke attributes—color, width, length, and orientation—from exemplar to animation frames. Building on the stroke transfer framework, we introduce features and basis fields capturing lighting-, view-, and geometry-dependent information, extending surface-based ones (e.g., intensity, apparent normals and curvatures, and distance from silhouettes) to volumetric scenes while supporting traditional surface objects. Novel features, including apparent relative velocity and mean free-path, address non-rigid flow and dynamic scenes. Our system combines automated exemplar selection, user-guided style learning, and temporally coherent stroke generation, enabling artistic and expressive visualizations of dynamic media.