Fast Image‐Space Silhouette Extraction for Non‐Photorealistic Landscape Rendering

Abstract

AbstractLandscape illustration, a core visualization technique for field geologists and geomorphologists, employs the parsimonious use of linework to represent surface structure in a straightforward and intuitive manner. Under the rubric of non‐photorealistic rendering (NPR), automated procedures in this vein render silhouettes and creases to represent, respectively, view‐dependent and view‐independent landscape features. This article presents two algorithms and implementations for rendering silhouettes from adaptive tessellations of point‐normal (PN) triangles at speeds approaching those suitable for animation. PN triangles use cubic polynomial models to provide a surface that appears smooth at any required resolution. The first algorithm, drawing on standard silhouette detection techniques in surface meshes, builds object space facet adjacencies and image space pixel adjacencies in the graphics pipeline following adaptive tessellation. The second makes exclusive use of image space analysis without referencing the underlying scene world geometry. Other than initial pre‐processing operations, recent advances in the OpenGL API allow implementations for both algorithms to be hosted entirely on the graphics processing unit (GPU), eliminating slowdowns through data transfer across the system memory bus. We show that both algorithms provide viable paths to real‐time animation of pen and ink style landscape illustrations but that the second demonstrates superior performance over the first.