多分辨率球体包装树:分层多分辨率三维数据结构

Jiro Inoue, A. J. Stewart
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引用次数: 2

摘要

自然界中经常出现球形堆积排列,它具有高效的空间填充和能量最小化特性。紧密的球体堆积可以在单一分辨率下提供紧密、均匀和高度对称的空间采样。我们介绍了多分辨率球体堆积树(MSP-tree):一种基于球体堆积排列的分层空间数据结构,适用于三维空间表示和选择性细化。与常用的八叉树相比,MSP-树有三个优点:扇出更低(比八叉树低四倍)、堆积更密集(密集度约为 24%)和持久性(粗分辨率下的球体中心在更高分辨率下依然存在)。我们提出的 MSP-tree 既是一种基于区域的方法,能简洁直观地描述细化机制,也是一种基于网格的方法,更适合实施。MSP-tree 是一种稳健、高度对称的三维空间细分方法,具有良好的图像处理特性。
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Multiresolution sphere packing tree: a hierarchical multiresolution 3D data structure
Sphere packing arrangements are frequently found in nature, exhibiting efficient space-filling and energy minimization properties. Close sphere packings provide a tight, uniform, and highly symmetric spatial sampling at a single resolution. We introduce the Multiresolution Sphere Packing Tree (MSP-tree): a hierarchical spatial data structure based on sphere packing arrangements suitable for 3D space representation and selective refinement. Compared to the commonly used octree, MSP-tree offers three advantages: a lower fanout (a factor of four compared to eight), denser packing (about 24% denser), and persistence (sphere centers at coarse resolutions persist at finer resolutions). We present MSP-tree both as a region-based approach that describes the refinement mechanism succintly and intuitively, and as a lattice-based approach better suited for implementation. The MSP-tree offers a robust, highly symmetric tessellation of 3D space with favorable image processing properties.
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