PCL学习笔记Day5

滤波-体素栅格和随机采样

//滤波
#include<pcl/io/pcd_io.h>
#include<pcl/point_types.h>
// 包含相关头文件
#include<pcl/filters/voxel_grid.h>
#include<pcl/filters/uniform_sampling.h>
// 可视化展示
#include<pcl/visualization/pcl_visualizer.h>
using namespace std;
typedef pcl::PointXYZ PointT;
int main() {
    
    
	// 读取点云
	pcl::PointCloud<PointT>::Ptr cloud(new pcl::PointCloud<PointT>);
	pcl::io::loadPCDFile("rabbit.pcd", *cloud);
	pcl::visualization::PCLVisualizer viewer1;
	viewer1.addPointCloud(cloud, "cloud2");
	std::cout << "original cloud size : " << cloud->size() << std::endl;
	//使用体素化网格（Voxelgrid）进行下采样
	//pcl::VoxelGrid<PointT> grid;// 创建滤波对象
	//const float leaf = 0.5f;
	//grid.setLeafSize(leaf, leaf, leaf);//设置体素体积
	//grid.setInputCloud(cloud);//设置点云
	//pcl::PointCloud<PointT>::Ptr voxelResult(new pcl::PointCloud<PointT>);
	//grid.filter(*voxelResult);//执行滤波，输出结果
	// 使用随机采样

	pcl::visualization::PCLVisualizer viewer;
	pcl::UniformSampling<PointT> uniform_sampling;
	uniform_sampling.setInputCloud(cloud);
	double radius = 0.005f;
	uniform_sampling.setRadiusSearch(radius);
	pcl::PointCloud<PointT>::Ptr uniformResult(new pcl::PointCloud<PointT>);
	uniform_sampling.filter(*uniformResult);
	std::cout << "UniformSampling size :" << uniformResult->size() << std::endl;
	pcl::visualization::PointCloudColorHandlerCustom<PointT> red(uniformResult, 255, 0, 0);

	viewer.addPointCloud(uniformResult, red, "cloud1");
	cout << "voxel downsample size :" << uniformResult->size() << endl;
	viewer.spin();
	system("pause");
	return 0;
   
}

参考链接：https://github.com/MNewBie/PCL-Notes/blob/master/chapter2.md

https://zhuanlan.zhihu.com/p/268524083