Fluid Simulation as a Tool for Painterly Animation

1. Fluid Simulation as a Tool for Painterly Animation Other details Our stroke based rendering system follows the basic template introduced in Processing images and video for an impressionist effect. We use a quality controlled Delaunay triangulation to control stroke density. We clip strokes to region boundaries, and apply random permutations to stroke color and width. We can create videos by processing each frame of a source video clip, or by generating multiple renderings from a single source image. We draw curved brush strokes by advecting a point through the brush alignment field. We use vorticity confinement forces to exaggerate the turbulent effects in our fluid fields. The brush stroke settings can vary between regions; we may use different stroke textures and permutation ranges in different regions. The idea We love the turbulent brush stroke patterns in Starry Night, and we wanted to develop NPR algorithms that would give us a similar effect. We combined a stroke based rendering system with vector fields from a semi-Lagrangian fluid simulation. Image Regions and Vector Fields We split the source image into regions using a color space clustering method. For each region, we specify a vector field which will control stroke alignment. If we’re making videos, we define a second field that controls stroke motion. The types of fields that we use are: TPS Fields: We use the region definitions to imply a set of vectors tangent to the region boundaries. Those vectors become control points for a pair of thin plate splines. The result is a smooth vector field that is neatly aligned to the region boundaries. Fluid Velocity Fields: We use a semi-Lagrangian fluid simulation to create a dynamic velocity field. Currently we’re using forces derived from the TPS control points to initialize the fields, but we’re looking for other interesting ways to setup or influence the fluid fields. Hybrid Fields: Fields defined as a weighted sum of the fluid and TPS fields, where the weights are a function of the distance from the nearest TPS control point. Optical Flow Fields: When working with video, advecting the strokes via an optical flow field can make them seem to “stick” to objects in the video. Fluid velocity fields for the poppy demo TPS Fields for the poppy demo Application binaries, source code, and additional demos and discussion available at:http://www.sccs.swarthmore.edu/users/03/sven/npr  Fluid fields have interesting eddies and evolve smoothly over time.  TPS fields are aligned to region boundaries.  With hybrid fluid/TPS fields we try to get the best of both worlds. Sven C. Olsen (sven2718@verizon.net)Bruce A. Maxwell (maxwell@swarthmore.edu) Swarthmore College