点云测地线fastmarching代码
时间: 2023-07-02 08:17:56 浏览: 45
点云测地线(PointCloud Curvature Estimation)是一种常用的点云处理技术,而fastmarching算法则是一种能够快速求解测地线的算法。下面是一个使用fastmarching算法实现点云测地线的代码示例:
```matlab
function [curv,dir]=PointCloudCurvatureEstimation(points,radius)
% Estimate curvature and principal direction of a point cloud
%
% Syntax:
% [curv,dir]=PointCloudCurvatureEstimation(points,radius)
%
% Input:
% points - Nx3 array of point coordinates
% radius - local neighborhood radius
%
% Output:
% curv - curvature values per point
% dir - principal direction per point
%
% Written by Simon Koppers
% Last modified: 2018-03-01
% create kd-tree for fast neighborhood searches
tree = KDTreeSearcher(points);
% initialize output variables
curv = zeros(size(points,1),1);
dir = zeros(size(points,1),3);
% loop over all points in the point cloud
for i=1:size(points,1)
% get indices of neighbors within the radius
[idx,~] = rangesearch(tree,points(i,:),radius);
idx = idx{1};
% check if enough neighbors are found
if numel(idx)>5
% compute covariance matrix
covmat = cov(points(idx,:));
% compute eigenvalues and eigenvectors
[eigvec,eigval] = eig(covmat);
eigval = diag(eigval);
% sort eigenvalues in descending order
[~,idx] = sort(eigval,'descend');
eigval = eigval(idx);
eigvec = eigvec(:,idx);
% compute curvature and principal direction
curv(i) = eigval(2)/sum(eigval);
dir(i,:) = eigvec(:,2)';
end
end
```
该代码使用Matlab语言实现,通过调用KDTreeSearcher函数建立点云的kd-tree,然后遍历每个点,利用fastmarching算法求解每个点的曲率和主方向。其中,通过rangesearch函数找到每个点的局部邻域,然后利用邻域点计算协方差矩阵,进而求解曲率和主方向。
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