Conventional digital painting systems rely on procedural rules and physical simulation to render paint strokes. We present an interactive, data-driven painting system that uses scanned images of real natural media to synthesize both new strokes and complex stroke interactions, obviating the need for physical simulation. First, users capture images of real media, including examples of isolated strokes, pairs of overlapping strokes, and smudged strokes. Online, the user inputs a new stroke path, and our system synthesizes its 2D texture appearance with optional smearing or smudging when strokes overlap. We demonstrate high-fidelity paintings that closely resemble the captured media style, and also quantitatively evaluate our synthesis quality via user studies.

@article{Lu:2013:RPW,
   author = "Jingwan Lu and Connelly Barnes and Stephen DiVerdi and Adam Finkelstein",
   title = "{RealBrush}: Painting with Examples of Physical Media",
   journal = "ACM Transactions on Graphics (Proc. SIGGRAPH)",
   year = "2013",
   month = aug
}