IEEE Computer Graphics and Applications

• PrePrint: Incremental, Approximate Database Queries and Uncertainty for Exploratory Visualization
  Exploratory data visualization allows analysts to interactively select queries on a dataset, and can help them rapidly find interesting results. On very large datasets, however, queries slow down to a point where analysts cannot explore. Incremental queries operate on progressively large samples from a database; the visualization updates to show the latest results, and can be annotated to show expected confidence intervals. In this article, we explore how users interact with incremental visualizations. First, we work with analysts to understand how they interact with approximate incremental bar charts, and find challenges with traditional error-bar approaches. We then present guidelines for incremental approximate visualizations, and several charts that convey uncertainty differently, including a visualization tuned to comparison.
  
  
  
  
• PrePrint: Fast Rendering of Diffusion Curves with Triangles
  Diffusion curves are a new kind of primitive in vector graphics, capable of representing smooth color transitions among boundaries. Their rendering requires solving Poisson's equation, and many previous efforts relied on traditional solvers which commonly require GPU acceleration to achieve real-time rasterization. This obviously restricts deployment on the internet, e.g. as Rich Internet Applications (RIAs), in which various computing environments are involved. Inspired by the observation that diffusion effects have very similar appearance to locally defined interpolation with particular orientation and magnitude, we propose a mesh-based approach combined with mean value coordinates (MVC) interpolant to efficiently render diffusion curve images on CPU. A visibility algorithm is employed to efficiently find and sort neighboring curve nodes for each vertex, and then the colors of vertices are assigned according to MVC interpolation with neighboring curve nodes. Our experiments show comparable rendering results to traditional solvers, while our method is computationally more efficient and runs much faster on a CPU.
  
  
  
  
• PrePrint: A Practical Workflow for Making Anatomical Atlases in Biological Research
  The anatomical atlas has been at the intersection of science and art for centuries. These atlases are essential to biological research, but high quality atlases are often lacking. Recent advances in imaging technology have made high quality 3-dimensional (3D) atlases possible. However, until now there has been a lack of practical workflows using standard tools to generate atlases from images of biological samples. With certain adaptations, the computer graphics (CG) artist’s workflow and tools, traditionally used in the film industry, are practical for building high quality biological atlases. We present a workflow explicitly applied to the generation of a 3D anatomical atlas using accessible artist’s tools and describe a detailed example of building a mouse limb atlas for studying the development of the mouse musculoskeletal system. It is hoped that our work will raise the awareness of using artist’s tools in scientific research and promote interdisciplinary collaborations between artists and scientists.
  
  
  
  
• PrePrint: Using Visualization and Data Analysis to Understand Critical Structures in Massive Time Varying Turbulent Flow Simulations
  Turbulence, the most common state of fluid motion in nature and engineering, represents a Grand Challenge for the physical and computer sciences. To capture the wide range of non-linearly interacting three-dimensional fluctuations typical of applications, we need to use the most powerful supercomputers available. Of particular importance is the concept of small-scale universality which is critical not only to our fundamental understanding but also to model and predict turbulent flows. Two important descriptors of small-scale motions are the energy dissipation rate and vorticity. Although it is known that intense vorticity and dissipation tend to concentrate in filamentary and sheet-like structures respectively, their evolution is much less understood or quantified. This paper details the crucial role that visualization and data analysis play in analyzing and understanding turbulent flow simulations at 4096^3 cells per time slice (= 68 billion cells) and 17 time slices (= 1 trillion total cells). The visualization techniques presented in this paper allow us to investigate the dynamics of intense events individually or as they form clusters. Understanding the geometrical and dynamical descriptions of these intense events allow scientists to get closer to a more complete understanding of turbulent flows and more accurate models for engineering applications.
  
  
  
  
• IEEE Computer Graphics and Applications - May-June 2012 (Vol. 32, No. 3)
  IEEE Computer Graphics and Applications
  
  
  
  
• PrePrint: A Graph Algebra For Visual Analytics
  Visual analytics, which combines analytical techniques with advanced visualization features, is fast becoming a standard tool in extracting information from graph data. Many tools have been developed for this purpose, suggesting a need for formal methods to guide the creation of such tools. Increased data demands on computing will require redesign of visual analytic tool paradigms to consider performance and reliability in the context of analysis at exascale. Further, there is a need for visual analysts to document their analysis, for scalability, reuse, and result justification. To address these needs, we develop a visual analytic graph framework encapsulated in a formal algebra for graph data and introduce its atomic operators, which include selection and aggregation. A framework we build around this algebra employs visual operators and supports dynamic attributes of data to enable scalable visual exploration of data. We present an example implementation of the algebra and demonstrate its benefits in scalable and parallel programmability of systems.
  
  
  
  
• PrePrint: Geometric Quantification of Features in Large Flow Fields
  Interactive exploration of flow features in large-scale 3D unsteady flow data is one of the most challenging problems in visualization today. In an effort to comprehensively explore the complex feature spaces in these datasets, we have designed a scalable framework for investigating a multitude of characteristics from traced fieldlines. This new capability has allowed us to examine various neighborhood-based geometric attributes in concert with other scalar quantities, a type of analysis that was not previously possible due to the large computational overhead and I/O requirements. We have integrated visual analytics methods into our approach by allowing users to procedurally and interactively describe and extract high-level flow features. In this work, we show the generality and expressiveness that is offered by this approach, and we show its efficacy by exploring various phenomena in a large global ocean modeling simulation.
  
  
  
  
• PrePrint: A VR Simulator for Intra-Cardiac Interventional Procedure: Concept, Design and Implementation
  The process of learning diagnosis and minimally invasive treatment of heart diseases takes substantial time due to the complex nature of the diseases and the high skill set required to manipulate surgical devices, especially in percutanous intra-cardiac cases. We are interested to develop a novel simulator to create a realistic and low-cost training environment for intra-cardiac intervention. This paper focuses on the concept, design and implementation of a Virtual Reality (VR) simulator for intra-cardiac intervention. Instead of using traditional Finite Element Method (FEM), a new geometrical-based method is proposed to model the interaction between an intra-cardiac catheter and the heart wall. A boundary-enhanced voxelization technique is developed to accelerate the process for detecting catheter-heart interactions. A tactile interface is designed incorporating a VR catheter unit to track the catheter movement within the virtual heart. A progressive approach is implemented to reconstruct the heart chamber for the application of heart mapping.
  
  
  
  
• PrePrint: A Simulation System for Training Catheterization Skills Based on a Fast Multigrid Solver
  A virtual reality based simulation system is proposed to help trainees develop skills for catheterization, which is one of the fundamental but difficult procedures in vascular interventional radiology. We develop a deformable model to simulate complicated behaviors of guidewires and catheters based on the principle of minimum total potential energy. A fast and stable multigrid solver is proposed to ensure both realistic simulation and real time interaction. In addition, we develop geometrically and topologically accurate vascular models based on improved parallel transport frames and implement an efficient collision detection scheme. A series of experiments are conducted to evaluate our multigrid solver in terms of stability, time performance, the capability of simulating catheter behaviors and the realism of catheter deformation. An empirical study is also designed based on a typical selective catheterization procedure to assess the feasibility and effectiveness of the proposed system.
  
  
  
  
• PrePrint: Practical Noise Reduction for Progressive Stochastic Ray Tracing with Perceptual Control
  We present a method to reduce noise in stochastic ray tracing that is especially tailored to interactive progressive rendering. High-variance light paths are accumulated in a separate buffer, which is filtered by a high-quality edge preserving filter. Then a combination of the noisy unfiltered samples and the less noisy (but biased) filtered samples is added to the low-variance samples in order to form the final image. A novel per-pixel blending operator combines both contributions in a way that respects a user-defined threshold on perceived noise. Our method is able to provide fast, reliable previews, even in the presence of complex features like specular surfaces and high-frequency textures. At the same time it is consistent in the sense that the bias due to filtering vanishes in the limit.