Incremental Poisson Surface Reconstruction for Large Scale Three-Dimensional Modeling
Yu, Qiang1,2; Sui, Wei2; Wang, Ying2; Xiang, Shiming1,2; Pan, Chunhong2
2019-11
会议名称Chinese Conference on Pattern Recognition and Computer Vision
会议日期2019-11
会议地点陕西省西安市
摘要

A novel Incremental Poisson Surface Reconstruction (IPSR) method based on point clouds and the adaptive octree is proposed in this paper. It solves two problems of the most popular Poisson Surface Reconstruction (PSR) method. First, the PSR is time and memory consuming when treating large scale scenes with millions of points. Second, the PSR can hardly handle the incremental reconstruction for scenes with newly arrived points, unless being restarted on all points. In our method, large scale point clouds are first partitioned into small neighboring blocks. By providing an octree node classification mechanism, the Poisson equation is reformulated with boundary constraints to achieve the seamless reconstruction between adjacent blocks. Solving the Poisson equation with boundary constraints, the indicator function is obtained and the surface mesh is extracted. Experiments on different types of datasets verify the effectiveness and the efficiency of our method.

关键词Surface reconstruction Large scale point cloud Incremental
收录类别EI
语种英语
七大方向——子方向分类三维视觉
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/46624
专题多模态人工智能系统全国重点实验室_先进时空数据分析与学习
中国科学院自动化研究所
通讯作者Yu, Qiang
作者单位1.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Yu, Qiang,Sui, Wei,Wang, Ying,et al. Incremental Poisson Surface Reconstruction for Large Scale Three-Dimensional Modeling[C],2019.
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