搜索资源列表
NormFet_WindowsXP_src
- 计算点云数据的法向量和局部特征,以备三维重建运用-The normals and features can be computed from a point cloud using the NormFet software
Survey-on-normal-estimation
- 三维点云法向量估计综述，由于获取方便、表示简单、灵活等优势，点云逐渐成为常用的三维模型表示方法之一-Point clouds are becoming more and more common for the representation of 3D geometry models because of its advantages over mesh models
calcMeshNormals
- 用于求取三维点云数据的法向量，我的人脸建模就是用的这个，效果很好，但必须保证点云没有重叠的，否则会出现严重错误。-Strike a 3D point cloud data for normal vectors, and my face is to use this model, the effect is very good, but must ensure that there is no overlap of the point c
PoissonRecon
- 用于点云表面重建，基于Poisson重建算法，生成.ply文件，需要先求取点云法向量。-For point cloud surface reconstruction, reconstruction algorithm based on Poisson generate. Ply files, you need to strike a point cloud normal vector.
PCA
- 用主成分分析法估计出点云中每点的法向量函数-Principal component analysis method for normal estimation in point cloud
faxiangliang
- 点云三维重建中需要用的法向量计算，能够有效避免法向量不一致的问题，更好进行三维重建。测试有用。-Normal vector calculation point cloud reconstruction in need, and can effectively avoid the problem of inconsistent normals, better three-dimensional reconstruction. Useful
L-M(CPP)
- L_M非线性算法。根据平面点云数据进行平面拟合，得到平面的法向量，效果很好。-L_M methods.The plane fitting based on the planar point cloud data, get the normal vector of the plane, the effect is very good.
PtsCompress
- 点云读取，建立包围盒，进行K领域搜索，法向量计算-Point cloud, reading, creating a bounding box, perform the search field K, vector calculation method
NormalEsimation2
- 求点云的法向量和k近邻的求取，可以根据一些需要自己改写，自己建立工程后可以使用-about the normalesimation ,after the debug can be excute in vs
ICP-point-cloud-registration
- 三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 -Th
point3d
- 直接运行TestMyCrust.m, 读取点云txt,或者直接加载mat文件 运行需要几分钟，耐心等待 完成后运行trianglenormal.m, 生成三角面片的法向量 运行完成得到tri.txt（组成三角面片的点的编号信息）,trinormal.txt(每个三角面片法向量数值)，diandian.txt(每个点云信息) 然后将三个数据当做stl_gen.exe的输入文件，得到trisuface.stl文件(run TestM
Normal_estimation
- 基于PCL的估算散乱点云的法矢量，并进行颜色渲染显示(estimation of normal vectors for point clouds and color rendering display based on PCL)
point_cloud
- 用经典的pca k邻域方法估计点云法向量的程序，带有matlab gui，使用matlab 2016b编译运行成功，输入点云最好为列向量的txt文件，gui中内置了点云显示模块以及生成的点云法向量显示，并且可以输出法向量到txt文件中。(The program of estimating point cloud vector with the classical PCA K neighborhood method, with Matla
用主成分分析法估计出点云中每点的法向量函数
- 用主成分分析法估计出点云中每点的法向量函数，实现平台为matlab(Principal component analysis is used to estimate the normal vector function of every point in point cloud, and the platform is matlab.)
normnd
- matlab代码，可以计算点云中的法向向量，可用于检测点云中的平面等(Calculating normal vectors of point clouds)
normal
- 通过构建四叉树，通过邻域搜索方法计算点云中每个点的法向量并进行展示(By constructing quadtree, the normal vector of each point in the point cloud was calculated and displayed by neighborhood search method)
k-近邻点估计点云法向量
- 利用matlab实现k-近邻点估计点云法向量求解，(Matlab is used to solve the normal vector of k-nearest neighbor point cloud.)
基于法向量的点云数据精简算法仿真
- 点云数据精简程序简单易懂！matlab算法——计算三维散乱点云的曲率，包括主曲率，高斯曲率和平均曲率(Reduced algorithm of laser measurement data for geometric parameters of ring forgings based on Artificial Immune Algorithm.)
FPFH-SAC-ICP
- 特征点提取，法向量估计，fpfh描叙特征点，SAC-IA粗配准。ICP精确配准(Feature point extraction, normal vector estimation, FPFH descr iption of feature points, sac-ia rough registration. Accurate registration of ICP)
estimate_normal
- 计算点云表面的法线向量(computes the vector normal of surface of the point cloud)