Relief impostor selection for large scale urban rendering

Image-based rendering techniques are often the preferred choice to accelerate the exploration of massive outdoor models and complex human-made structures. In the last few years, relief mapping has been shown to be extremely useful as a compact representation of highly-detailed 3D models. In this paper we describe a rendering system for interactive, high-quality visualization of large scale urban models through a hierarchical collection of properly-oriented relief-mapped polygons. At the heart of our approach is a visibilityaware algorithm for the selection of the set of viewing planes supporting the relief maps. Our selection algorithm optimizes both the sampling density and the coverage of the relief maps and its running time is mostly independent on the underlying geometry. We show that our approach is suitable for navigating through large scale urban models at interactive rates while preserving both geometric and appearance details.Postprint (published version

A Survey of GPU-Based Large-Scale Volume Visualization

This survey gives an overview of the current state of the art in GPU techniques for interactive large-scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga-, tera-, and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out-of-core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e., “output-sensitive” algorithms and system designs. This leads to recent outputsensitive approaches that are “ray-guided,” “visualization-driven,” or “display-aware.” In this survey, we focus on these characteristics and propose a new categorization of GPU-based large-scale volume visualization techniques based on the notions of actual output-resolution visibility and the current working set of volume bricks—the current subset of data that is minimally required to produce an output image of the desired display resolution. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we discuss in this survey.Engineering and Applied Science