| 摘要: |
| 针对法向信息缺失和采样点缺失的带有洞的散乱点云数据，提出了一种高效、高质量的多层同步表面重建方法.首先利用动态等高线检测出含有洞的八叉树节点，并且基于HPR（hidden point removal）映射计算出八叉树顶点的内外状态，建立带有顶点内外标识的空间有向状态八叉树，然后基于八叉树节点内法向测试方法保证基于k近邻表面重建过程中采样点的法向的正确性，且该空间有向状态八叉树可以支持不同层次的点云同步重建，在保证重建结果正确性的前提下，提高重建效率. |
| 关键词: 表面重建 点云 状态八叉树 k近邻 HPR |
| DOI：10.13328/j.cnki.jos.005078 |
| 分类号: |
| 基金项目:国家自然科学基金（61472224，61472225）；山东省自主创新及成果转化专项（2014ZZCX08201）；山东大学青年学者未来计划（2015WLJH41）；泰山学者建设工程专项经费 |
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| Multi-Layers Surface Reconstruction Method for Point Set with Holes |
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WANG Xiao-Ting1,2, WANG Lu1,2, MENG Xiang-Xu1,2
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1.School of Computer Science and Technology, Shandong University, Ji'nan 250101, China;2.Engineering Research Center of Digital Media Technology, Ministry of Education, Ji'nan 250101, China
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| Abstract: |
| This paper proposes a multi-layer surface reconstruction method based on a special oriented status octree. The method is designed to handle point sets with missing normal information and with holes. First, the octree cells distributed on holes are detected by active contours. By using hidden point removal (HPR) operator, the inside or outside status of each corner of octree cells are calculated, and the mono-oriented status octree is constructed. Then the normal direction of the initial points set inside the status octree is determined by in-cell normal detection method, and the parallel multi-layer surface reconstruction from k-nearest neighbors is carried out by using the status octree. The proposed method improves the construction efficiency while guaranteeing the construction quality. |
| Key words: surface reconstruction point set status octree k-nearest neighbors HPR |
