MLS移动最小二乘法

———————–【转自： SimpleTriangle】——————————–
移动最小二乘法对点云进行平滑处理，数据重采样，并且可以计算优化的估计法线,还可以用来曲面重建

#include <pcl/point_types.h>#include <pcl/io/pcd_io.h>#include <pcl/kdtree/kdtree_flann.h>#include <pcl/surface/mls.h>#include <pcl/console/time.h>#include <pcl/point_cloud.h>using namespace std;typedef pcl::PointXYZ point;typedef pcl::PointCloud<point> pointcloud;int main (int argc,char **argv){        pointcloud::Ptr cloud (new pointcloud);        pcl::io::loadPCDFile(argv[1],*cloud);        cout<<"points size is:"<<cloud->size()<<endl;        pcl::search::KdTree<point>::Ptr tree (new pcl::search::KdTree<point>);        //创建存储的mls对象        // pcl::PointCloud<pcl::PointNormal> mls_points;         pcl::PointCloud<point> mls_points;        //创建mls对象        //  pcl::MovingLeastSquares<point,pcl::PointNormal> mls;        pcl::MovingLeastSquares<point,point> mls;        mls.setComputeNormals(true);        mls.setInputCloud(cloud);        mls.setPolynomialFit(true); //设置为true则在平滑过程中采用多项式拟合来提高精度        mls.setPolynomialOrder(2); //MLS拟合的阶数，默认是2        mls.setSearchMethod(tree);        mls.setSearchRadius(1.1);  //这个值越大，输出的点越多        mls.process(mls_points);        cout<<"mls poits size is: "<<mls_points.size()<<endl;        // Save output        pcl::io::savePCDFile ("mid-mls.pcd", mls_points);}return 0;