865 research outputs found

    The State of the Art in Flow Visualization: Dense and Texture-Based Techniques

    Get PDF
    Flow visualization has been a very attractive component of scientific visualization research for a long time. Usually very large multivariate datasets require processing. These datasets often consist of a large number of sample locations and several time steps. The steadily increasing performance of computers has recently become a driving factor for a reemergence in flow visualization research, especially in texture-based techniques. In this paper, dense, texture-based flow visualization techniques are discussed. This class of techniques attempts to provide a complete, dense representation of the flow field with high spatio-temporal coherency. An attempt of categorizing closely related solutions is incorporated and presented. Fundamentals are shortly addressed as well as advantages and disadvantages of the methods. Categories and Subject Descriptors (according to ACM CCS): I.3 [Computer Graphics]: visualization, flow visualization, computational flow visualizatio

    Doctor of Philosophy

    Get PDF
    dissertationVisualizing surfaces is a fundamental technique in computer science and is frequently used across a wide range of fields such as computer graphics, biology, engineering, and scientific visualization. In many cases, visualizing an interface between boundaries can provide meaningful analysis or simplification of complex data. Some examples include physical simulation for animation, multimaterial mesh extraction in biophysiology, flow on airfoils in aeronautics, and integral surfaces. However, the quest for high-quality visualization, coupled with increasingly complex data, comes with a high computational cost. Therefore, new techniques are needed to solve surface visualization problems within a reasonable amount of time while also providing sophisticated visuals that are meaningful to scientists and engineers. In this dissertation, novel techniques are presented to facilitate surface visualization. First, a particle system for mesh extraction is parallelized on the graphics processing unit (GPU) with a red-black update scheme to achieve an order of magnitude speed-up over a central processing unit (CPU) implementation. Next, extending the red-black technique to multiple materials showed inefficiencies on the GPU. Therefore, we borrow the underlying data structure from the closest point method, the closest point embedding, and the particle system solver is switched to hierarchical octree-based approach on the GPU. Third, to demonstrate that the closest point embedding is a fast, flexible data structure for surface particles, it is adapted to unsteady surface flow visualization at near-interactive speeds. Finally, the closest point embedding is a three-dimensional dense structure that does not scale well. Therefore, we introduce a closest point sparse octree that allows the closest point embedding to scale to higher resolution. Further, we demonstrate unsteady line integral convolution using the closest point method

    GPUFLIC: interactive and accurate dense visualization of unsteady flows

    Get PDF
    Journal ArticleAbstract The paper presents an efficient and accurate implementation of Unsteady Flow LIC (UFLIC) on the Graphics Processing Unit (GPU). We obtain the same, high quality texture representation of unsteady two-dimensional flows as the original, time-consuming method but leverage the features of today's commodity hardware to achieve interactive frame rates. Despite a remarkable number of recent contributions in the field of texture-based visualization of time-dependent vector fields, the present paper is the first to provide a faithful implementation of that prominent technique fully supported by the graphics pipeline

    Image Space Advection on graphics hardware

    Get PDF
    www.icg.tu-graz.ac.at The scientific visualization and computer graphics communities have witnessed a tremendous rise in graphics processing unit (GPU) related literature and methodology recently. This is due in part to the rapidly increasing processing speed offered by graphics cards. Parallel to this, we have seen several advances made in the area of texture-based flow visualization. We present a texture-based flow visualization technique, Image Space Advection (ISA), that takes advantage of the computing power offered by recent, state-of-theart GPUs. We have implemented a completely GPU-based version of the ISA algorithm. Here we describe our implementation in detail, including both the advantages and disadvantages of implementing ISA on the GPU. The result is state-of-the-art technique that demonstrates the latest in terms of both flow visualization methodology and GPU programming

    Visualization of flow fields in the web platform

    Get PDF
    Visualization of vector fields plays an important role in research activities nowadays -- Web applications allow a fast, multi-platform and multi-device access to data, which results in the need of optimized applications to be implemented in both high-performance and low-performance devices -- Point trajectory calculation procedures usually perform repeated calculations due to the fact that several points might lie over the same trajectory -- This paper presents a new methodology to calculate point trajectories over highly-dense and uniformly-distributed grid of points in which the trajectories are forced to lie over the points in the grid -- Its advantages rely on a highly parallel computing architecture implementation and in the reduction of the computational effort to calculate the stream paths since unnecessary calculations are avoided, reusing data through iterations -- As case study, the visualization of oceanic currents through in the web platform is presented and analyzed, using WebGL as the parallel computing architecture and the rendering Application Programming Interfac

    Flow charts: visualization of vector fields on arbitrary surfaces

    Get PDF
    Journal ArticleWe introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance

    Two-dimensional unsteady flow visualization by animating evenly-spaced streamlets

    Get PDF
    Flow visualization has been widely used to display and discover patterns and features in vector fields. Common applications include the representation of ocean currents and weather model data. In this thesis, a flexible method for animating vector fields is developed, based on a generalization of a Poisson disc sampling method. The algorithm has two stages; in the first streamlets are drawn into an image buffer, larger than their intended size. Before they are drawn they are tested to see if they impact on already drawn areas; if they do, they are rejected. In the second stage the ones that pass the test are drawn normal size. The concept of a 3D streamlet object, which groups consecutive time step streamlets as a primitive rendering object, is introduced as part of a method for animating streamlets so that they have minimal overlap and show frame-to-frame coherence providing visual continuity when animating time varying vector fields. Acceptance schemes that allow for occasional overlap between streamlets are explored and found to improve both the speed and the overall quality. Both model data and real weather data are used to evaluate the method. The results show that the method produces good results and is flexible, allows for variable size and density of streamlets, and produces good results
    corecore