4,266 research outputs found

    Image-space visibility ordering for cell projection volume rendering of unstructured data

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    MaterialVis: Material visualization tool using direct volume and surface rendering techniques

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    Cataloged from PDF version of article.Visualization of the materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called Material Vis. Unlike the existing tools, Material Vis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. Material Vis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, Material Vis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography. (C) 2014 Elsevier Inc. All rights reserved

    Efficient algorithms for occlusion culling and shadows

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    The goal of this research is to develop more efficient techniques for computing the visibility and shadows in real-time rendering of three-dimensional scenes. Visibility algorithms determine what is visible from a camera, whereas shadow algorithms solve the same problem from the viewpoint of a light source. In rendering, a lot of computational resources are often spent on primitives that are not visible in the final image. One visibility algorithm for reducing the overhead is occlusion culling, which quickly discards the objects or primitives that are obstructed from the view by other primitives. A new method is presented for performing occlusion culling using silhouettes of meshes instead of triangles. Additionally, modifications are suggested to occlusion queries in order to reduce their computational overhead. The performance of currently available graphics hardware depends on the ordering of input primitives. A new technique, called delay streams, is proposed as a generic solution to order-dependent problems. The technique significantly reduces the pixel processing requirements by improving the efficiency of occlusion culling inside graphics hardware. Additionally, the memory requirements of order-independent transparency algorithms are reduced. A shadow map is a discretized representation of the scene geometry as seen by a light source. Typically the discretization causes difficult aliasing issues, such as jagged shadow boundaries and incorrect self-shadowing. A novel solution is presented for suppressing all types of aliasing artifacts by providing the correct sampling points for shadow maps, thus fully abandoning the previously used regular structures. Also, a simple technique is introduced for limiting the shadow map lookups to the pixels that get projected inside the shadow map. The fillrate problem of hardware-accelerated shadow volumes is greatly reduced with a new hierarchical rendering technique. The algorithm performs per-pixel shadow computations only at visible shadow boundaries, and uses lower resolution shadows for the parts of the screen that are guaranteed to be either fully lit or fully in shadow. The proposed techniques are expected to improve the rendering performance in most real-time applications that use 3D graphics, especially in computer games. More efficient algorithms for occlusion culling and shadows are important steps towards larger, more realistic virtual environments.reviewe

    Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP

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    Cataloged from PDF version of article.Direct volume visualization is an important method in many areas, including computational fluid dynamics and medicine. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multicore parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm supports progressive rendering. We compared the GPU implementation with the serial and multicore implementations. We observed significant speed-ups that, together with progressive rendering, enables reaching interactive rates for large datasets

    Time-varying volume visualization

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    Volume rendering is a very active research field in Computer Graphics because of its wide range of applications in various sciences, from medicine to flow mechanics. In this report, we survey a state-of-the-art on time-varying volume rendering. We state several basic concepts and then we establish several criteria to classify the studied works: IVR versus DVR, 4D versus 3D+time, compression techniques, involved architectures, use of parallelism and image-space versus object-space coherence. We also address other related problems as transfer functions and 2D cross-sections computation of time-varying volume data. All the papers reviewed are classified into several tables based on the mentioned classification and, finally, several conclusions are presented.Preprin

    Visibility rendering order: Improving energy efficiency on mobile GPUs through frame coherence

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    During real-time graphics rendering, objects are processed by the GPU in the order they are submitted by the CPU, and occluded surfaces are often processed even though they will end up not being part of the final image, thus wasting precious time and energy. To help discard occluded surfaces, most current GPUs include an Early-Depth test before the fragment processing stage. However, to be effective it requires that opaque objects are processed in a front-to-back order. Depth sorting and other occlusion culling techniques at the object level incur overheads that are only offset for applications having substantial depth and/or fragment shading complexity, which is often not the case in mobile workloads. We propose a novel architectural technique for mobile GPUs, Visibility Rendering Order (VRO), which reorders objects front-to-back entirely in hardware by exploiting the fact that the objects in graphics animated applications tend to keep its relative depth order across consecutive frames (temporal coherence). Since order relationships are already tested by the Depth Test, VRO incurs minimal energy overheads because it just requires adding a small hardware to capture that information and use it later to guide the rendering of the following frame. Moreover, unlike other approaches, this unit works in parallel with the graphics pipeline without any performance overhead. We illustrate the benefits of VRO using various unmodified commercial 3D applications for which VRO achieves 27% speed-up and 14.8% energy reduction on average over a state-of-the-art mobile GPU.Peer ReviewedPostprint (author's final draft

    The Video Mesh: A Data Structure for Image-based Video Editing

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    This paper introduces the video mesh, a data structure for representing video as 2.5D "paper cutouts." The video mesh allows interactive editing of moving objects and modeling of depth, which enables 3D effects and post-exposure camera control. The video mesh sparsely encodes optical flow as well as depth, and handles occlusion using local layering and alpha mattes. Motion is described by a sparse set of points tracked over time. Each point also stores a depth value. The video mesh is a triangulation over this point set and per-pixel information is obtained by interpolation. The user rotoscopes occluding contours and we introduce an algorithm to cut the video mesh along them. Object boundaries are refined with perpixel alpha values. The video mesh is at its core a set of texture mapped triangles, we leverage graphics hardware to enable interactive editing and rendering of a variety of effects. We demonstrate the effectiveness of our representation with a number of special effects including 3D viewpoint changes, object insertion, and depth-of-field manipulation

    Doctor of Philosophy

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    dissertationDataflow pipeline models are widely used in visualization systems. Despite recent advancements in parallel architecture, most systems still support only a single CPU or a small collection of CPUs such as a SMP workstation. Even for systems that are specifically tuned towards parallel visualization, their execution models only provide support for data-parallelism while ignoring taskparallelism and pipeline-parallelism. With the recent popularization of machines equipped with multicore CPUs and multi-GPU units, these visualization systems are undoubtedly falling further behind in reaching maximum efficiency. On the other hand, there exist several libraries that can schedule program executions on multiple CPUs and/or multiple GPUs. However, due to differences in executing a task graph and a pipeline along with their APIs being considerably low-level, it still remains a challenge to integrate these run-time libraries into current visualization systems. Thus, there is a need for a redesigned dataflow architecture to fully support and exploit the power of highly parallel machines in large-scale visualization. The new design must be able to schedule executions on heterogeneous platforms while at the same time supporting arbitrarily large datasets through the use of streaming data structures. The primary goal of this dissertation work is to develop a parallel dataflow architecture for streaming large-scale visualizations. The framework includes supports for platforms ranging from multicore processors to clusters consisting of thousands CPUs and GPUs. We achieve this in our system by introducing the notion of Virtual Processing Elements and Task-Oriented Modules along with a highly customizable scheduler that controls the assignment of tasks to elements dynamically. This creates an intuitive way to maintain multiple CPU/GPU kernels yet still provide coherency and synchronization across module executions. We have implemented these techniques into HyperFlow which is made of an API with all basic dataflow constructs described in the dissertation, and a distributed run-time library that can be used to deploy those pipelines on multicore, multi-GPU and cluster-based platforms

    Hardware and software improvements of volume splatting

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    This paper proposes different hardware-based acceleration of the three classical splatting strategies: emph{composite-every-sample}, emph{object-space sheet-buffer} and emph{image-space sheet-buffer}.Preprin
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