Renderings of volumetric data have become an important data analysis tool for applications ranging from medicine to scientific simulation. We propose a volumetric drawing system that directly extracts sparse linear features, such as silhouettes and suggestive contours, using a temporally coherent seed-and-traverse framework. In contrast to previous methods based on isosurfaces or nonrefractive transparency, producing these drawings requires examining an asymptotically smaller subset of the data, leading to efficiency on large data sets. In addition, the resulting imagery is often more comprehensible than standard rendering styles, since it focuses attention on important features in the data. We test our algorithms on datasets up to $512^3$, demonstrating interactive extraction and rendering of line drawings in a variety of drawing styles.

@article{Burns:2005:LDF,
   author = "Michael Burns and Janek Klawe and Szymon Rusinkiewicz and Adam
      Finkelstein and Doug DeCarlo",
   title = "Line Drawings from Volume Data",
   journal = "ACM Transactions on Graphics (Proc. SIGGRAPH)",
   year = "2005",
   month = aug,
   volume = "24",
   number = "3",
   pages = "512--518"
}