修正点云法向量二义性的泊松重建  

Poisson Reconstruction Correcting Ambiguity of Point Cloud Normal Vectors

作　　者：宋宏戈 杨瑞峰 郭晨霞 Song Hongge;Yang Ruifeng;Guo Chenxia(School of Instrument and Electronics,North University of China,Taiyuan 030051,Shanxi,China;Automated Test Equipment and System Engineering Technology Research Center of Shanci Province,Taiyuan 030051,Shanri,China)

机构地区：[1]中北大学仪器与电子学院,山西太原030051 [2]山西省自动化检测装备与系统工程技术研究中心,山西太原030051

出　　处：《应用激光》2024年第11期183-190,共8页Applied Laser

基　　金：山西省中央引导地方科技发展自由探索类基础研究项目(YDZJSX2022A027)。

摘　　要：由于三维点云在泊松重建时计算出来的法向量具有二义性,从而导致重构出来的曲面存在误差,故提出一种修正法线二义性的泊松曲面重建算法。计算输入所有点云的法向量,选取点云曲率最小点作为原点,将其法向量规定为正方向,通过KD树搜索近邻点,重定其近邻点的法线方向,然后再将其近邻点作为新的原点进行传播,从而修正法线的二义性问题,完成点云整体定向,最后根据得到的法向量对点云进行泊松重建。通过观察和定量分析可得,该算法能够大大削弱法线的二义性问题,重建出较好的曲面,对于3个模型最大偏差距离误差分别减少了66%、86%、95%。Ambiguity in the calculation of normal vectors during Poisson surface reconstruction of 3D point clouds can lead to errors in the reconstructed surface.This paper introduces a modified Poisson surface reconstruction algorithm designed to address the ambiguity of normal vectors.The algorithm calculates the normal vectors of all input point clouds,selects the point with the smallest curvature as the origin,defines its normal vector as the positive direction,searches for neighboring points using the KD tree,reorients the normal direction of neighboring points,and then regards its neighbor points as the new origin to correct the ambiguity of the normal and complete the overall orientation of the point cloud,and finally the algorithm reconstructs the surface according to the obtained normal vectors.Observations and quantitative analysis show that the algorithm significant reduces the ambiguity of normal vectors and can reconstruct a better surface,reducing the maximum deviation distance errors of three models by 66%,86%,and 95%respectively.

关 键 词：点云 二义性 法向量重定向 泊松曲面重建 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]