1.首先包含的对应的ModelCoefficients.h以及filter中向平面投影的project_inlier.h #include iostream#include pcl/io/pcd_io.h#include pcl/point_types.h#include pcl/ModelCoefficients.h#include pcl/filters/project_inliers.h 2.创建点
1.首先包含的对应的ModelCoefficients.h以及filter中向平面投影的project_inlier.h
#include <iostream> #include <pcl/io/pcd_io.h> #include <pcl/point_types.h> #include <pcl/ModelCoefficients.h> #include <pcl/filters/project_inliers.h>
2.创建点云对象指针并初始化,输出到屏幕
/2.初始化该对象 ? cloud->width? = 5;//对于未组织的点云的相当于points个数 ? cloud->height = 1; //对未组织的点云指定为1 ? cloud->points.resize (cloud->width * cloud->height); //修剪或追加值初始化的元素 ? for (size_t i = 0; i < cloud->points.size (); ++i) ? { ??? cloud->points[i].x = 1024 * rand () / (RAND_MAX + 1.0f); ??? cloud->points[i].y = 1024 * rand () / (RAND_MAX + 1.0f); ??? cloud->points[i].z = 1024 * rand () / (RAND_MAX + 1.0f); ? } ? // 3.cerr 输出对象放置刷屏 ? std::cerr << "Cloud before projection: " << std::endl; ? for (size_t i = 0; i < cloud->points.size (); ++i) ??? std::cerr << "??? " << cloud->points[i].x << " " ??????????????????????? << cloud->points[i].y << " " ??????????????????????? << cloud->points[i].z << std::endl;
//投影前点 `Cloud before projection: 1.28125 577.094 197.938 828.125 599.031 491.375 358.688 917.438 842.563 764.5 178.281 879.531 727.531 525.844 311.281
3.设置ModelCoefficients值。在这种情况下,我们使用一个平面模型,其中ax + by + cz + d = 0,其中a = b = d = 0,c = 1,或者换句话说,XY平面
? // 4.创建一个系数为X=Y=0,Z=1的平面 ? pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients ()); ? coefficients->values.resize (4); ? coefficients->values[0] = coefficients->values[1] = 0; ? coefficients->values[2] = 1.0; ? coefficients->values[3] = 0;
4.通过该滤波将所有的点投影到创建的平面上,并输出结果
** 注意这里在使用的时候再创建滤波后对象不规范,应该放在程序开始的时候**
? //5.创建滤波后对象,并通过滤波投影,并显示结果 ? pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_projected(new pcl::PointCloud<pcl::PointXYZ>); ? // 创建滤波器对象 ? pcl::ProjectInliers<pcl::PointXYZ> proj; ? proj.setModelType (pcl::SACMODEL_PLANE); ? proj.setInputCloud (cloud); ? proj.setModelCoefficients (coefficients); ? proj.filter (*cloud_projected); ? std::cerr << "Cloud after projection: " << std::endl; ? for (size_t i = 0; i < cloud_projected->points.size (); ++i) ??? std::cerr << "??? " << cloud_projected->points[i].x << " " ??????????????????????? << cloud_projected->points[i].y << " " ??????????????????????? << cloud_projected->points[i].z << std::endl; ? return (0);
//投影后点 Cloud before projection: 1.28125 577.094 197.938 828.125 599.031 491.375 358.688 917.438 842.563 764.5 178.281 879.531 727.531 525.844 311.281 Cloud after projection: 1.28125 577.094 0 828.125 599.031 0 358.688 917.438 0 764.5 178.281 0 727.531 525.844 0
6.参考网址
pcl官网例程
all-in_one 中的有api 以及例子,但是具体理论说明还是参考官网吧!
...\PCL-1.8.1-AllInOne-msvc2017-win64(1)\share\doc\pcl-1.8\tutorials\sources中 例子要比pcl入门精通要全