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002:pcl 点云投影

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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

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