ROS PCL 点云处理学习之二 Downsampling a PointCloud using a VoxelGrid filter

mkdir test2
cd test2
touch voxel_grid.cpp 
gedit voxel_grid.cpp  

#include 
#include 
#include 
#include 

int
main (int argc, char** argv)
{
  pcl::PCLPointCloud2::Ptr cloud (new pcl::PCLPointCloud2 ());
  pcl::PCLPointCloud2::Ptr cloud_filtered (new pcl::PCLPointCloud2 ());

  // Fill in the cloud data
  pcl::PCDReader reader;
  // Replace the path below with the path where you saved your file
  reader.read ("table_scene_lms400.pcd", *cloud); // Remember to download the file first!

  std::cerr << "PointCloud before filtering: " << cloud->width * cloud->height 
       << " data points (" << pcl::getFieldsList (*cloud) << ").";

  // Create the filtering object
  pcl::VoxelGrid sor;
  sor.setInputCloud (cloud);
  sor.setLeafSize (0.01f, 0.01f, 0.01f);
  sor.filter (*cloud_filtered);

  std::cerr << "PointCloud after filtering: " << cloud_filtered->width * cloud_filtered->height 
       << " data points (" << pcl::getFieldsList (*cloud_filtered) << ").";

  pcl::PCDWriter writer;
  writer.write ("table_scene_lms400_downsampled.pcd", *cloud_filtered, 
         Eigen::Vector4f::Zero (), Eigen::Quaternionf::Identity (), false);

  return (0);
}

touch CMakeList.txt 
gedit CMakeList.txt 

cmake_minimum_required(VERSION 2.8 FATAL_ERROR)

project(voxel_grid)

find_package(PCL 1.2 REQUIRED)

include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})

add_executable (voxel_grid voxel_grid.cpp)
target_link_libraries (voxel_grid ${PCL_LIBRARIES})

结果为 ：

PointCloud before filtering: 460400 data points (x y z intensity distance sid)
PointCloud after filtering: 41049 data points (x y z intensity distance sid)