直通滤波-使用 PassThrough 过滤器过滤 PointCloud

本文链接：https://blog.youkuaiyun.com/m0_71087087/article/details/141949885

代码：创建一个文件，比如说，在你的收藏夹中编辑器，并将以下内容放入其中：passthrough.cpp

#include <iostream>
#include <pcl/point_types.h>
#include <pcl/filters/passthrough.h>

int
 main ()
{
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>);

  // Fill in the cloud data
  cloud->width  = 5;
  cloud->height = 1;
  cloud->points.resize (cloud->width * cloud->height);

  for (auto& point: *cloud)
  {
    point.x = 1024 * rand () / (RAND_MAX + 1.0f);
    point.y = 1024 * rand () / (RAND_MAX + 1.0f);
    point.z = 1024 * rand () / (RAND_MAX + 1.0f);
  }

  std::cerr << "Cloud before filtering: " << std::endl;
  for (const auto& point: *cloud)
    std::cerr << "    " << point.x << " "
                        << point.y << " "
                        << point.z << std::endl;

  // Create the filtering object
  pcl::PassThrough<pcl::PointXYZ> pass;
  pass.setInputCloud (cloud);
  pass.setFilterFieldName ("z");
  pass.setFilterLimits (0.0, 1.0);
  //pass.setNegative (true);
  pass.filter (*cloud_filtered);

  std::cerr << "Cloud after filtering: " << std::endl;
  for (const auto& point: *cloud_filtered)
    std::cerr << "    " << point.x << " "
                        << point.y << " "
                        << point.z << std::endl;

  return (0);
}

解释

现在，让我们逐个分解代码。

在以下几行中，我们定义 Point Clouds 结构，填写 input cloud，并将其内容显示到屏幕。

 // Fill in the cloud data
  cloud->width  = 5;
  cloud->height = 1;
  cloud->points.resize (cloud->width * cloud->height);

  for (auto& point: *cloud)
  {
    point.x = 1024 * rand () / (RAND_MAX + 1.0f);
    point.y = 1024 * rand () / (RAND_MAX + 1.0f);
    point.z = 1024 * rand () / (RAND_MAX + 1.0f);
  }

  std::cerr << "Cloud before filtering: " << std::endl;
  for (const auto& point: *cloud)
    std::cerr << "    " << point.x << " "
                        << point.y << " "
                        << point.z << std::endl;

然后，我们创建 PassThrough 过滤器对象，并设置其参数。这筛选条件字段名称设置为 Z 坐标，并且接受的间隔值设置为（0.0;1.0).

  pcl::PassThrough<pcl::PointXYZ> pass;
  pass.setInputCloud (cloud);
  pass.setFilterFieldName ("z");
  pass.setFilterLimits (0.0, 1.0);
  //pass.setNegative (true);
  pass.filter (*cloud_filtered);

最后，我们显示筛选后的云的内容。

  std::cerr << "Cloud after filtering: " << std::endl;
  for (const auto& point: *cloud_filtered)
    std::cerr << "    " << point.x << " "
                        << point.y << " "
                        << point.z << std::endl;

编译和运行程序：

将以下行添加到您的 CMakeLists.txt 文件中：

cmake_minimum_required(VERSION 3.5 FATAL_ERROR)

project(passthrough)

find_package(PCL 1.2 REQUIRED)

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

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

创建可执行文件后，您可以运行它。只需：

$ ./passthrough

您将看到类似于以下内容的内容：

Cloud before filtering:
    0.352222 -0.151883 -0.106395
    -0.397406 -0.473106 0.292602
    -0.731898 0.667105 0.441304
    -0.734766 0.854581 -0.0361733
    -0.4607 -0.277468 -0.916762
Cloud after filtering:
    -0.397406 -0.473106 0.292602
    -0.731898 0.667105 0.441304

过滤过程的图形显示如下所示。