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Selective refinement queries for volume visualization of unstructured tetrahedral meshes

机译:选择性细化查询,用于非结构化四面体网格的体积可视化

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We address the problem of the efficient visualization of large irregular volume data sets by exploiting a multiresolution model based on tetrahedral meshes. Multiresolution models, also called Level-Of-Detail (LOD) models, allow encoding the whole data set at a virtually continuous range of different resolutions. We have identified a set of queries for extracting meshes at variable resolution from a multiresolution model, based on field values, domain location, or opacity of the transfer function. Such queries allow trading off between resolution and speed in visualization. We define a new compact data structure for encoding a multiresolution tetrahedral mesh built through edge collapses to support selective refinement efficiently and show that such a structure has a storage cost from 3 to 5.5 times lower than standard data structures used for tetrahedral meshes. The data structures and variable resolution queries have been implemented together with state-of-the art visualization techniques in a system for the interactive visualization of three-dimensional scalar fields defined on tetrahedral meshes. Experimental results show that selective refinement queries can support interactive visualization of large data sets.
机译:我们通过利用基于四面体网格的多分辨率模型来解决大型不规则体积数据集的有效可视化问题。多分辨率模型也称为详细程度(LOD)模型,可以在几乎连续的不同分辨率范围内对整个数据集进行编码。我们已经基于字段值,域位置或传递函数的不透明度确定了一组查询,用于从多分辨率模型中以可变分辨率提取网格。这样的查询允许在分辨率和可视化速度之间进行权衡。我们定义了一种新的紧凑型数据结构,用于编码通过边缘折叠构建的多分辨率四面体网格,以有效地支持选择性细化,并表明这种结构的存储成本比用于四面体网格的标准数据结构低3到5.5倍。数据结构和可变分辨率查询已与最先进的可视化技术一起在用于对四面体网格上定义的三维标量场进行交互式可视化的系统中实现。实验结果表明,选择性细化查询可以支持大数据集的交互式可视化。

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