Institute for Data Analysis and Visualization

We present an isosurface generation algorithm for large-scale volumetric scattered data. Rather than construct a global tessellation of the data points, we dene a set of local tetrahedrizations that are guaranteed to cover the domain. Inside each local tetrahedrization, a point-based isosurface contouring algorithm is applied to generate isosurface geometry. Our work differs from previous work in that we make very few assumptions about the density of the point distribution, and we construct visual representations of the data directly without global tessellation or resampling. The merit of such an approach is a fairly general method that produces faithful renderings of large-scale scientic data.