We present a new adaptive sampling strategy for ray tracing. Our technique is specifically designed to handle multidimensional sample domains, and it is well suited for efficiently generating images with effects such as soft shadows, motion blur, and depth of field. These effects are problematic for existing image based adaptive sampling techniques as they operate on pixels, which are possibly noisy results of a Monte Carlo ray tracing process. Our sampling technique operates on samples in the multidimensional space given by the rendering equation and as a consequence the value of each sample is noise-free. Our algorithm consists of two passes. In the first pass we adaptively generate samples in the multidimensional space, focusing on regions where the local contrast between samples is high. In the second pass we reconstruct the image by integrating the multidimensional function along all but the image dimensions. We perform a high quality anisotropic reconstruction by determining the extent of each sample in the multidimensional space using a structure tensor. We demonstrate our method on scenes with a 3 to 5 dimensional space, including soft shadows, motion blur, and depth of field. The results show that our method uses fewer samples than Mittchell's adaptive sampling technique while producing images with less noise.

This paper presents a technique for acquiring the shape of real-world objects with complex isotropic and anisotropic reflectance. Our method estimates the local normal and tangent vectors at each pixel in a reference view from a sequence of images taken under varying point lighting. We show that for many real-world materials and a restricted set of light positions, the 2D slice of the BRDF obtained by fixing the local view direction is symmetric under reflections of the halfway vector across the normal-tangent and normal-binormal planes. Based on this analysis, we develop an optimization that estimates the local surface frame by identifying these planes of symmetry in the measured BRDF. As with other photometric methods, a key benefit of our approach is that the input is easy to acquire and is less sensitive to calibration errors than stereo or multi-view techniques. Unlike prior work, our approach allows estimating the surface tangent in the case of anisotropic reflectance. We confirm the accuracy and reliability of our approach with analytic and measured data, present several normal and tangent fields acquired with our technique, and demonstrate applications to appearance editing.

Transient faults due to particle strikes are a key challenge in microprocessor design. Driven by exponentially increasing transistor counts, per-chip faults are a growing burden. To protect against soft errors, redundancy techniques such as redundant multithreading (RMT) are often used. However, these techniques assume that the probability that a structural fault will result in a soft error (i.e., the Architectural Vulnerability Factor (AVF)) is 100 percent, unnecessarily draining processor resources. Due to the high cost of redundancy, there have been efforts to throttle RMT at runtime. To date, these methods have not incorporated an AVF model and therefore tend to be ad hoc. Unfortunately, computing the AVF of complex microprocessor structures (e.g., the ISQ) can be quite involved.

This paper presents a method for efficient compression and relighting with high-resolution, precomputed light transport matrices. We accomplish this using a 4D wavelet transform, transforming the columns of the transport matrix, in addition to the 2D row transform used in previous work. We show that a standard 4D wavelet transform can actually inflate portions of the matrix, because high-frequency lights lead to high-frequency images that cannot easily be compressed. Therefore, we present an adaptive 4D wavelet transform that terminates at a level that avoids inflation and maximizes sparsity in the matrix data. Finally, we present an algorithm for fast relighting from adaptively compressed transport matrices. Combined with a GPU-based precomputation pipeline, this results in an image and geometry relighting system that performs significantly better than 2D compression techniques, on average 2x-3x better in terms of storage cost and rendering speed for equal quality matrices.

Sampling distributions with blue noise characteristics are widely used in computer graphics. Although Poisson-disk distributions are known to have excellent blue noise characteristics, they are generally regarded as too computationally expensive to generate in real time. We present a new method for sampling by dart-throwing in O(N log N ) time and introduce a novel and efficient variation for generating Poisson-disk distributions in O(N) time and space.

The TreeJuxtaposer system [MGT*03] allowed visual comparison of large trees with guaranteed visibility of landmarks and Focus+Context navigation. While that system allowed exploration and comparison of larger datasets than previous work, it was limited to a single tree of 775,000 nodes by a large memory footprint. In this paper, we describe the theoretical limitations to TreeJuxtaposer's architecture that severely restrict its scalability. We provide two scalable, robust solutions to these limitations: TJC and TJC-Q. TJC is a system that supports browsing trees up to 15 million nodes by exploiting leading-edge graphics hardware while TJC-Q allows browsing trees up to 5 million nodes on commodity platforms. Both of these systems use a fast new algorithm for drawing and culling and benefit from a complete redesign of all data structures for more efficient memory usage and reduced preprocessing time.

We present a system for enhancing observation of user interactions in virtual environments. In particular, we focus on analyzing behavior patterns in the popular team-based first-person perspective game Return to Castle Wolfenstein: Enemy Territory. This game belongs to a genre characterized by two moderate-sized teams (usually 6 to 12 players each) competing over a set of objectives. Our system allows spectators to visualize global features such as large-scale behaviors and team strategies, as opposed to the limited, local view that traditional spectating modes provide. We also add overlay visualizations of semantic information related to the action that might be important to a spectator in order to reduce the information overload that plagues traditional overview visualizations. These overlays can visualize information about abstract concepts such as player distribution over time and areas of intense combat activity, and also highlight important features like player paths, fire coverage, etc. This added information allows spectators to identify important game events more easily and reveals large-scale player behaviors that might otherwise be overlooked.

We present a system for interactively producing exploded views of 3D architectural environments such as multi-story buildings. These exploded views allow viewers to simultaneously see the internal and external structures of such environments. To create an exploded view we analyze the geometry of the environment to locate individual stories. We then use clipping planes and multipass rendering to separately render each story of the environment in exploded form. Our system operates at the graphics driver level and therefore can be applied to existing OpenGL applications, such as first-person multi-player video games, without modification. The resulting visualization allows users to understand the global structure of architectural environments and to observe the actions of dynamic characters and objects interacting within such environments.

No abstract available.

We describe Chromium, a system for manipulating streams of graphics API commands on clusters of workstations. Chromium's stream filters can be arranged to create sort-first and sort-last parallel graphics architectures that, in many cases, support the same applications while using only commodity graphics accelerators. In addition, these stream filters can be extended programmatically, allowing the user to customize the stream transformations performed by nodes in a cluster. Because our stream processing mechanism is completely general, any cluster-parallel rendering algorithm can be either implemented on top of or embedded in Chromium. In this paper, we give examples of real-world applications that use Chromium to achieve good scalability on clusters of workstations, and describe other potential uses of this stream processing technology. By completely abstracting the underlying graphics architecture, network topology, and API command processing semantics, we allow a variety of applications to run in different environments.

We describe WireGL, a system for scalable interactive rendering on a cluster of workstations. WireGL provides the familiar OpenGL API to each node in a cluster, virtualizing multiple graphics accelerators into a sort-first parallel renderer with a parallel interface. We also describe techniques for reassembling an output image from a set of tiles distributed over a cluster. Using flexible display management, WireGL can drive a variety of output devices, from standalone displays to tiled display walls. By combining the power of virtual graphics, the familiarity and ordered semantics of OpenGL, and the scalability of clusters, we are able to create time-varying visualizations that sustain rendering performance over 70,000,000 triangles per second at interactive refresh rates using 16 compute nodes and 16 rendering nodes.

We describe a novel distributed graphics system that allows an application to render to a large tiled display. Our system, called WireGL, uses a cluster of off-the-shelf PCs connected with a high-speed network. WireGL allows an unmodified existing application to achieve scalable output resolution on such a display. This paper presents an efficient sorting algorithm which minimizes the network traffic for a scalable display. We will demonstrate that for most applications, our system provides scalable output resolution with minimal performance impact.

Recent interest in large displays has led to renewed development of tiled displays, which are comprised of several individual displays arranged in an array and used as one large logical display. Stanford's "Interactive Mural" is an example of such a display, using an overlapping four by two array of projectors that back-project onto a diffuse screen to form a 6' by 2' display area with a resolution of over 60 dpi. Writing software to make effective use of the large display space is a challenge because normal window system interaction metaphors break down. One promising approach is to switch to immersive applications; another approach, the one we are investigating, is to emulate office, conference room or studio environments which use the space to display a collection of visual material to support group activities. We describe a virtual graphics system that is designed to support multiple simultaneous rendering streams from both local and remote sites. The system abstracts the physical number of computers, graphics subsystems and projectors used to create the display. We provide performance measurements to show that the system scales well and thus supports a variety of different hardware configurations. The system is also interesting because it uses transparent "layers", instead of windows, to manage the screen.