Rendering Vector Data over Global, Multi-resolution 3D Terrain

Figure 3: Adaptation of the reference mesh to scan data using feature mesh refinement: a initial defective target mesh from range scans with landmarks added; b source mesh and

In particular, if refine(S ,i) is applied to each face F i of the mesh, we in fact perform a uniform refinement step and the resulting control mesh has to be identical to the

Figure 4 shows the tooth data set rendered with gradient- magnitude opacity-modulation, direct volume rendering us- ing a clipping plane, and context-preserving volume render- ing

Figure 1: Flow of data through our system: A base mesh is loaded; The sketching component allows the user to place feature curves on the surface of the mesh (red); The

For a parallel computation of the rendering cost, each render node computes the SAT only for the portion of the image space for which it computed the rendering cost.. Then each

While preprocessing solves the problem of expensive neighbor- hood data acquisition during rendering, the vast amount of generated data does still not allow interactive volume

Real-time rendering of terrain data needs to address three major aspects: data representation, surface rendering, and level of detail techniques.. Traditionally, terrain

With this work, we introduce an unstructured data volume rendering algorithm which is composed entirely of data-parallel primitives.. We compare the algorithm to community