This paper presents a forward mapping rendering algo-rithm to display regular volumetric grids that may not have the same spacings in the three grid directions. It takes advantage of the fact that convolution can be thought of as distributing energy from input samples into space. The renderer calculates an image plane footprint for each data sample and uses the footprint to spread the sample's energy onto the image plane. A result of the technique is that the forward mapping algorithm can support perspective without excessive cost, and support adaptive resampling of the three-dimensional data set during image generation.

This paper describes a new technique that efficiently combines volume rendering and scanline a-buffer tech-niques. This technique is useful for combining all types of volume-rendered objects with scanline ren-dered objects and is especially useful for rendering scenes containing gaseous phenomena such as clouds, fog, and smoke. The rendering and animation of these phenomena has been a difficult problem in computer graphics. A new algorithm for realistically modeling and an-imating gaseous phenomena is presented, providing true three-dimensional volumes of gas. The gases are modeled using turbulent flow based solid textur-ing to define their geometry and are animated based on turbulent flow simulations. A low albedo illu-mination model is used that takes into consideration self-shadowing of the volumes.

In this dissertation is presented a practical approach of the Projected Tetrahedra’s (PT) algorithm for interactive volume rendering of unstructured data using programmable graphics cards. Unlike similar works reported earlier, the proposed method employs two fragment shaders, one for computing the tetrahedra projections and another for rendering the volume. The proposed algorithm achieve interactive rates by storing the model in texture memory and avoiding redundant projections of the earlier implementations using vertex shaders. The algorithm is capable of rendering over 2 millions tetrahedra per second on current graphics hardware, making it competitive with recent ray casting approaches, while occupying a substantially smaller memory footprint. 1.

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In this paper we present a system for visualizing volume data from remote supercomputers �PermWeb�. We have developed both parallel volume rendering algorithms, and the World Wide Web software for accessing the data at the remote sites. The implementation uses Hypertext Markup Language �HTML�, Java, and Common GatewayIn terface �CGI � scripts to connect World Wide Web �WWW � servers�clients to our volume renderers. The front ends are interactive Java classes for speci�cation of view, shading, and classi�cation inputs. We present performance results, and implementation details for connections to our computing resources at the University of California Santa Cruz including a MasPar MP-2, SGI Reality Engine-RE2, and SGI Challenge machines. We apply the system to the task of visualizing trabecular bone from �nite element simulations. Fast volume rendering on remote compute servers through a web interface allows us to increase the accessibility of the results to more users. User interface issues, overviews of parallel algorithm developments, and overall system interfaces and protocols are presented. Access is available through Uniform Resource Locator �URL�

Clouds are an important aspect of rendering outdoor scenes. This paper describes a cloud system that extends texture splatting on particles to model a dozen cloud types (e.g., stratus, cumulus congestus, cumulonimbus), an improvement over earlier systems that modeled only one type of cumulus. We also achieve fast real-time rendering, even for scenes of dense overcast coverage, which was a limitation for previous systems. We present a new shading model that uses artist-driven controls rather than a programmatic approach to approximate lighting. This is suitable when fine-grained control over the look-and-feel is necessary, and artistic resources are available. We also introduce a way to simulate cloud formation and dissipation using texture splatted particles.

Modeling and animating complex volumetric natural phenomena, such as clouds, is a difficult task. Most systems are difficult to use, require adjustment of numerous, complex parameters, and are non-interactive. Therefore, we have developed an intuitive, interactive system to artistically model, animate, and render visually convincing volumetric clouds using modern consumer graphics hardware. Our natural, high-level interface models volumetric clouds through the use of qualitative cloud attributes. The animation of the implicit skeletal structures and independent transformation of octaves of noise emulate various environmental conditions. The resulting interactive design, rendering, and animation system produces perceptually convincing volumetric cloud models that can be used in interactive systems or exported for higher quality offline rendering.

We present a practical system to visualize large datasets interactively on commodity PCs. Interactive visualization has applications in many areas, including computeraided design, engineering, entertainment, and training. Traditionally, visualization of large datasets has required expensive high-end graphics workstations. Recently, with the exponential trend of higher performance and lower cost of PC graphics cards, inexpensive PCs are becoming an attractive alternative to high-end machines. But a barrier in exploiting this potential is the small memory size of typical PCs. Our system uses new out-of-core techniques to visualize datasets much larger than main memory. In a preprocessing phase, we build a hierarchical decomposition of the dataset using an octree, precompute coefficients used for visibility determination, and create levels of detail. At runtime, we use multiple threads to overlap visibility computation, cache management, and rasterization. The structure of the octree and the visibility coefficients are kept in main memory. The contents of the octree nodes are loaded on demand from disk into a cache. To find the visible set, we use a fast approximate algorithm followed by a hardware-assisted conservative algorithm. To