计算机集成制造系统 ›› 2020, Vol. 26 ›› Issue (第4): 970-979.DOI: 10.13196/j.cims.2020.04.011

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运用边界状态约束的表面体素加密细分算法

刘晨燕1,敬石开1+,张伟1,2,赵芳垒1   

  1. 1.北京理工大学机械工程学院
    2.中国科学院计算技术研究所
  • 出版日期:2020-04-30 发布日期:2020-04-30
  • 基金资助:
    国家863计划资助项目(2015AA042505)。

Surfacevoxel refinement algorithm using boundary state constraints

  • Online:2020-04-30 Published:2020-04-30
  • Supported by:
    Project supported by the National High-Tech.R&D Program,China(No.2015AA042505).

摘要: 为了平衡体素模型的体素数量与精细度,提出一种实体模型体素加密细化算法。该算法对低分辨率均一体素模型的表面体素进行切分,标记与三角面不相交的体素,并运用边界状态传递判定标记体素的内外位置。通过编码不同八叉树的节点,并进行跨八叉树快速邻居节点搜寻,实现多级加密细分。实验结果表明,该算法可以以低分辨率模型为基础,精确地获得体素单元少的高分辨率模型。

关键词: 表面细分, 多分辨率, 体素化, 边界状态约束算法

Abstract: To balance the voxel number and surface fineness of voxel model,a refinement method for solid models was proposed.The surface voxels of the low-resolution uniform model were divided firstly,and sub-voxels not intersecting any triangle were marked.Boundary state constraints method was used to determine whether a marked voxel was inside or outside the model.Neighbor searching scheme across different octree nodes was achieved by encoding rules,which could realize multi-level refinement.The result showed that starting from the low-resolution voxel model,the proposed method could produce accurate high-resolution model with fewer voxels.

Key words: surface refinement, multi-scale resolution, voxelization, boundary state constraint algorithm

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