[人工智能]PCL学习笔记(17)——统计滤波方法

源码

#include <iostream>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/filters/statistical_outlier_removal.h>
#include <pcl/visualization/pcl_visualizer.h>

boost::shared_ptr<pcl::visualization::PCLVisualizer> simpleVis(pcl::PointCloud<pcl::PointXYZ>::ConstPtr cloud)
{
	//创建3D窗口并添加点云
	boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
	viewer->setBackgroundColor(0, 0, 0);
	viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud");
	viewer->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "sample cloud");
	viewer->addCoordinateSystem(1.0);
	viewer->initCameraParameters();
	return (viewer);
}
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>);
  // 填入点云数据
  pcl::PCDReader reader;
  // 把路径改为自己存放文件的路径
  reader.read<pcl::PointXYZ> ("table_scene_lms400.pcd", *cloud);
  std::cerr << "Cloud before filtering: " << std::endl;
  std::cerr << *cloud << std::endl;

  //可视化
  boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer;
  viewer = simpleVis(cloud);
  while (!viewer->wasStopped())
  {
	  viewer->spinOnce(100);
	  boost::this_thread::sleep(boost::posix_time::microseconds(100000));
  }

  // 创建滤波器对象
  pcl::StatisticalOutlierRemoval<pcl::PointXYZ> sor;
  sor.setInputCloud (cloud);
  sor.setMeanK (50);
  sor.setStddevMulThresh (1.0);
  sor.filter (*cloud_filtered);
  std::cerr << "Cloud after filtering: " << std::endl;
  std::cerr << *cloud_filtered << std::endl;

  //pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);
  boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer1;
  viewer1 = simpleVis(cloud_filtered);
  while (!viewer1->wasStopped())
  {
	  viewer1->spinOnce(100);
	  boost::this_thread::sleep(boost::posix_time::microseconds(100000));
  }

  pcl::PCDWriter writer;
  writer.write<pcl::PointXYZ> ("table_scene_lms400_inliers.pcd", *cloud_filtered, false);
  sor.setNegative (true);
  sor.filter (*cloud_filtered);
  writer.write<pcl::PointXYZ> ("table_scene_lms400_outliers.pcd", *cloud_filtered, false);
  return (0);
}