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Interactive Visualization of Very Large Datasets Using an Out-of-Core Point-based Approach

机译:使用基于核心点的方法的互动可视化非常大的数据集

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We present an out-of-core, point-based approach for inter-active rendering of very large volumetric datasets. Our approach is based on the assumption that the density of voxels with the same function-value in large discretized volumetric scalar fields is high enough to be used to render contour and volume approximations using points to represent the voxels. This approach allows us to visualize isovalue-structures in high-resolution datasets at full resolution and interactive frame rates. In a pre-processing step, we sort the voxels by function-value and store them in a file together with a look-up table for later interactive retrieval. The displayed voxelsets can then be changed in real tune by determining their locations in the file and loading them into memory. As we store position, and not function-value, the volumetric dimension of a dataset to be handled by our approach is limited by three factors: the number of points that can be rendered to achieve a sufficient frame rate, the number of bits used to store the position data, and the maximum file-size supported by the operating system. Depending on the spatial distribution of the voxels among the function-values selected, the result is either one or multiple contours or "isoclouds".
机译:我们介绍了一个基于核心的基于点的方法,用于非常大的体积数据集的主动渲染。我们的方法是基于假设具有在大离散体积标量标量字段中具有相同功能值的体素的密度足够高,以便用于使用点代表体素来呈现轮廓和体积近似。这种方法允许我们以全分辨率和交互式帧速率在高分辨率数据集中可视化Isovalue结构。在预处理步骤中,我们通过函数值对体素进行排序,并将其存储在文件中,将它们与查找表一起存储以供以后的交互式检索。然后,通过确定文件中的位置并将其加载到内存中,可以在实际调谐中更改显示的voxElset。当我们存储位置而不是功能值时,我们的方法处理数据集的体积维度是有限的三个因素:可以呈现的点数以获得足够的帧速率,用于的比特数存储位置数据,以及操作系统支持的最大文件大小。根据所选功能值之间的体素的空间分布,结果是一个或多个轮廓或“异框”。

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