Hybrid Grids for Sparse Volume Rendering

Stefan Zellmann, D. Meurer, U. Lang
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引用次数: 5

Abstract

Shallow k-d trees are an efficient empty space skipping data structure for sparse volume rendering and can be constructed in real-time for moderately sized data sets. Larger volume data sets however require deeper k-d trees that sufficiently cull empty space but take longer to construct. In contrast to k-d trees, uniform grids have inferior culling properties but can be constructed in real-time. We propose a hybrid data structure that employs hierarchical subdivision at the root level and a uniform grid at the leaf level to balance construction and rendering times for sparse volume rendering. We provide a thorough evaluation of this spatial index and compare it to state of the art space skipping data structures.
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稀疏体渲染的混合网格
浅k-d树是稀疏体绘制中一种有效的空空间跳过数据结构,可以实时构建中等大小的数据集。然而,更大容量的数据集需要更深的k-d树,它可以充分剔除空白空间,但需要更长的时间来构建。与k-d树相比,均匀网格具有较差的剔除特性,但可以实时构建。我们提出了一种混合数据结构,在根级采用分层细分,在叶级采用统一网格,以平衡稀疏体渲染的构造和渲染时间。我们对该空间索引进行了全面的评估,并将其与最先进的空间跳过数据结构进行了比较。
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