Wesley Griffin

Real-Time GPU Surface Curvature Estimation on Deforming Meshes and Volumetric Data Sets

Surface curvature is used in a number of areas in computer graphics, including texture synthesis and shape representation, mesh simplification, surface modeling, and nonphotorealistic line drawing. Most real-time applications must estimate curvature on a triangular mesh. This estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. However, as more computational work is done directly on the GPU, it is increasingly common for object geometry to exist only in GPU memory. Examples include vertex skinned animations and isosurfaces from GPU-based surface reconstruction algorithms. For static models, curvature can be precomputed and CPU algorithms are a reasonable choice. For deforming models where the geometry only resides on the GPU, transferring the deformed mesh back to the CPU limits performance. We introduce a GPU algorithm for estimating curvature in real time on arbitrary triangular meshes. We demonstrate our algorithm with curvature-based NPR feature lines and a curvature-based approximation for an ambient occlusion. We show curvature computation on volumetric data sets with a GPU isosurface extraction algorithm and vertex-skinned animations. We present a graphics pipeline and CUDA implementation. Our curvature estimation is up to {\sim}18{\times} faster than a multithreaded CPU benchmark.

GPU curvature estimation on deformable meshes

Surface curvature is used in a number of areas in computer graphics, including texture synthesis and shape representation, mesh simplification, surface modeling, and non-photorealistic line drawing. Most real-time applications must estimate curvature on a triangular mesh. This estimation has been limited to CPU algorithms, forcing object geometry to reside in main memory. However, as more computational work is done directly on the GPU, it is increasingly common for object geometry to exist only in GPU memory. Examples include vertex skinned animations and isosurfaces from GPU-based surface reconstruction algorithms. For static models, curvature can be pre-computed and CPU algorithms are a reasonable choice. For deforming models where the geometry only resides on the GPU, transferring the deformed mesh back to the CPU limits performance. We introduce a GPU algorithm for estimating curvature in real-time on arbitrary triangular meshes. We demonstrate our algorithm with curvature-based NPR feature lines and a curvature-based approximation for ambient occlusion. We show curvature computation on volumetric datasets with a GPU isosurface extraction algorithm and vertex-skinned animations. Our curvature estimation is up to ~18x faster than a multithreaded CPU benchmark.

Variable bit rate GPU texture decompression

Variable bit rate compression can achieve better quality and compression rates than fixed bit rate methods. None the less, GPU texturing uses lossy fixed bit rate methods like DXT to allow random access and on‐the‐fly decompression during rendering. Changes in games and GPUs since DXT was developed make its compression artifacts less acceptable, and texture bandwidth less of an issue, but texture size is a serious and growing problem. Games use a large total volume of texture data, but have a much smaller active set. We present a new paradigm that separates GPU decompression from rendering. Rendering is from uncompressed data, avoiding the need for random access decompression. We demonstrate this paradigm with a new variable bit rate lossy texture compression algorithm that is well suited to the GPU, including a new GPU‐friendly formulation of range decoding, and a new texture compression scheme averaging 12.4:1 lossy compression ratio on 471 real game textures with a quality level similar to traditional DXT compression. The total game texture set are stored in the GPU in compressed form, and decompressed for use in a fraction of a second per scene.

Objective image quality assessment of texture compression

Texture compression is widely used in real-time rendering to reduce storage and bandwidth requirements. Recent research in compression algorithms has explored both reduced fixed bit rate and variable bit rate algorithms. The results are evaluated at the individual texture level using Mean Square Error, Peak Signal-to-Noise Ratio, or visual image inspection. We argue this is the wrong evaluation approach. Compression artifacts in individual textures are likely visually masked in final rendered images and this masking is not accounted for when evaluating individual textures. This masking comes from both geometric mapping of textures onto models and the effects of combining different textures on the same model such as diffuse, gloss and bump maps. We evaluate final rendered images using rigorous perceptual error metrics. Our method samples the space of viewpoints in a scene, renders the scene from each viewpoint using variations of compressed textures, and then compares each to a ground truth using uncompressed textures from the same viewpoint. We show that masking has a significant effect on final rendered image quality, that graphics hardware compression algorithms are too conservative, and reduced bit rates are possible while maintaining quality.

Incorporating D3.js information visualization into immersive virtual environments

We have created an integrated interactive visualization and analysis environment that can be used immersively or on the desktop to study a simulation of microstructure development during hydration or degradation of cement pastes and concrete. Our environment combines traditional 3D scientific data visualization with 2D information visualization using D3.js running in a web browser. By incorporating D3.js, our visualization allowed the scientist to quickly diagnose and debug errors in the parallel implementation of the simulation.

Evaluating Texture Compression Masking Effects Using Objective Image Quality Assessment Metrics

Texture compression is widely used in real-time rendering to reduce storage and bandwidth requirements. Recent research in compression algorithms has explored both reduced fixed bit rate and variable bit rate algorithms. The results are evaluated at the individual texture level using mean square error, peak signal-to-noise ratio, or visual image inspection. We argue this is the wrong evaluation approach. Compression artifacts in individual textures are likely visually masked in final rendered images and this masking is not accounted for when evaluating individual textures. This masking comes from both geometric mapping of textures onto models and the effects of combining different textures on the same model such as diffuse, gloss, and bump maps. We evaluate final rendered images using rigorous perceptual error metrics. Our method samples the space of viewpoints in a scene, renders the scene from each viewpoint using variations of compressed textures, and then compares each to a ground truth using uncompressed textures from the same viewpoint. We show that masking has a significant effect on final rendered image quality, masking effects and perceptual sensitivity to masking varies by the type of texture, graphics hardware compression algorithms are too conservative, and reduced bit rates are possible while maintaining final rendered image quality.

A Critical Comparison of 3D Experiments and Simulations of Tricalcium Silicate Hydration

Advances in nano-computed X-ray tomography (nCT), nano X-ray fluorescence spectrometry (nXRF), and high-performance computing have enabled the first direct comparison between observations of three-dimensional nanoscale microstructure evolution during cement hydration and computer simulations of the same microstructure using HydratiCA. nCT observations of a collection of triclinic tricalcium silicate (Ca3SiO5) particles reacting in a calcium hydroxide solution are reported and compared to simulations that duplicate, as nearly as possible, the thermal and chemical conditions of those experiments. Particular points of comparison are the time dependence of the solid phase volume fractions, spatial distributions, and morphologies. Comparisons made at 7 h of reaction indicate that the simulated and observed volumes of Ca3SiO5 consumed by hydration agree to within the measurement uncertainty. The location of simulated hydration product is qualitatively consistent with the observations, but the outer envelope of hydration product observed by nCT encloses more than twice the volume of hydration product in the simulations at the same time. Simultaneous nXRF measurements of the same observation volume imply calcium and silicon concentrations within the observed hydration product envelope that are consistent with Ca(OH)2 embedded in a sparse network of calcium silicate hydrate (C-S-H) that contains about 70 % occluded porosity in addition to the amount usually accounted as gel porosity. An anomalously large volume of Ca(OH)2 near the particles is observed both in the experiments and in the simulations, and can be explained as originating from the hydration of additional particles outside the field of view. Possible origins of the unusually large amount of observed occluded porosity are discussed.

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants’ confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

Application creation for an immersive virtual measurement and analysis laboratory

Content creation for realtime interactive systems is a difficult problem. In game development, content creation pipelines are a major portion of the code base and content creation is a major portion of the budget. In research environments, the choice of rendering and simulation systems is frequently driven by the need for easy to use content authoring tools. In visualization, this problem is compounded by the widely varying types of data that users desire to visualize. We present a visualization application creation framework incorporated into our visualization system that enables measurement and quantitative analysis tasks in both desktop and immersive environments on diverse input data sets.

Validation of SplitVector encoding and stereoscopy for quantitative visualization of quantum physics data in virtual environments

We designed and evaluated SplitVector, a new vector field display approach to help scientists perform new discrimination tasks on scientific data shown in virtual environments (VEs). Our empirical study compared the SplitVector approach with three other approaches of direct linear representation, log, and text display common in information-rich VEs or IRVEs. Our results suggest the following: (1) SplitVectors improve the accuracy by about 10 times compared to the linear mapping and by 4 times to log in discrimination tasks; (2) SplitVectors lead to no significant differences from the IRVE text display approach, yet reduce the clutter; and (3) SplitVector improved task performance in both mono and stereoscopy conditions.