Wetbrush: GPU-Based 3D Painting Simulation at the Bristle Level

Abstract
We present a real-time painting system that simulates the interactions among brush, paint, and canvas at the bristle level. The key challenge is how to model and simulate sub-pixel paint details, given the limited computational resource in each time step. To achieve this goal, we propose to define paint liquid in a hybrid fashion: the liquid close to the brush is modeled by particles, and the liquid away from the brush is modeled by a density field. Based on this representation, we develop a variety of techniques to ensure the performance and robustness of our simulator under large time steps, including brush and particle simulations in non-inertial frames, a fixed-point method for accelerating Jacobi iterations, and a new Eulerian-Lagrangian approach for simulating detailed liquid effects. The resulting system can realistically simulate not only the motions of brush bristles and paint liquid, but also the liquid transfer processes among different representations. We implement the whole system on GPU by CUDA. Our experiment shows that artists can use the system to draw realistic and vivid digital paintings, by applying the painting techniques that they are familiar with but not offered by many existing systems.
Type
Publication
ACM Trans. Graph. (SIGGRAPH Asia), 34(6)
Non-Inertial Frame
Fluid Simulation
Fluid Coupling
Eulerian-Lagrangian
Brush and Hair
GPU Computing
FLIP/PIC
Authors
Chief Scientist
My research interests include computer graphics, computer vision, generative AI, and embodied AI.