怎么使用pointcloud库
时间: 2023-11-08 19:04:19 浏览: 43
PointCloud库是一个用于点云数据处理的C++库,可以用于读写、滤波、分割、配准、特征提取、可视化等操作。下面是几个使用PointCloud库的例子:
1. 读取点云数据
```
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
int main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
if (pcl::io::loadPCDFile<pcl::PointXYZ> ("cloud.pcd", *cloud) == -1) //* load the file
{
PCL_ERROR ("Couldn't read file cloud.pcd \n");
return (-1);
}
std::cout << "Loaded "
<< cloud->width * cloud->height
<< " data points from cloud.pcd with the following fields: "
<< std::endl;
for (size_t i = 0; i < cloud->points.size (); ++i)
std::cout << " " << cloud->points[i].x << " "
<< cloud->points[i].y << " "
<< cloud->points[i].z << std::endl;
return (0);
}
```
这段代码读取一个点云文件(.pcd格式),并打印出其中每一个点的坐标。
2. 点云滤波
```
#include <pcl/filters/voxel_grid.h>
int main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>);
// ... read or fill in the cloud data
pcl::VoxelGrid<pcl::PointXYZ> sor;
sor.setInputCloud (cloud);
sor.setLeafSize (0.1f, 0.1f, 0.1f);
sor.filter (*cloud_filtered);
std::cout << "PointCloud after filtering: "
<< cloud_filtered->width * cloud_filtered->height
<< " data points (" << pcl::getFieldsList (*cloud_filtered) << ").";
return (0);
}
```
这段代码使用了点云滤波器(VoxelGrid),将一个点云进行下采样,从而降低了点云数据的大小和复杂度。
3. 点云配准
```
#include <pcl/registration/icp.h>
int main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr source_cloud (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr target_cloud (new pcl::PointCloud<pcl::PointXYZ>);
// ... read or fill in the source and target cloud data
pcl::IterativeClosestPoint<pcl::PointXYZ, pcl::PointXYZ> icp;
icp.setInputSource (source_cloud);
icp.setInputTarget (target_cloud);
pcl::PointCloud<pcl::PointXYZ> transformed_source_cloud;
icp.align (transformed_source_cloud);
std::cout << "has converged:" << icp.hasConverged() << " score: " <<
icp.getFitnessScore() << std::endl;
std::cout << icp.getFinalTransformation() << std::endl;
return (0);
}
```
这段代码使用了点云配准算法(IterativeClosestPoint),将一个点云匹配到另一个点云上,并输出了配准后的点云变换矩阵和匹配得分。
4. 点云可视化
```
#include <pcl/visualization/cloud_viewer.h>
int main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
// ... read or fill in the cloud data
pcl::visualization::CloudViewer viewer ("Simple Cloud Viewer");
viewer.showCloud (cloud);
while (!viewer.wasStopped ())
{
}
return (0);
}
```
这段代码使用了点云可视化工具(CloudViewer),展示了一个点云的三维可视化效果,并且可以通过鼠标操作来旋转和缩放点云。