3d激光雷达开发（narf关键点）

Posted 2022-03-10 费晓行

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        所谓关键点，其实就是那些梯度信息特征比较明显的点。至于是多明显，这部分需要用数学公式来进行标识。第一次学的时候，可以先有一个感性的认识。pcl库给出的例子是从RangeImage中提取narf关键点，原代码地址在这，https://pcl.readthedocs.io/projects/tutorials/en/latest/narf_keypoint_extraction.html#narf-keypoint-extraction

1、准备narf.cpp文件

/* \\author Bastian Steder */

#include <iostream>

#include <pcl/range_image/range_image.h>
#include <pcl/io/pcd_io.h>
#include <pcl/visualization/range_image_visualizer.h>
#include <pcl/visualization/pcl_visualizer.h>
#include <pcl/features/range_image_border_extractor.h>
#include <pcl/keypoints/narf_keypoint.h>
#include <pcl/console/parse.h>
#include <pcl/common/file_io.h> // for getFilenameWithoutExtension

typedef pcl::PointXYZ PointType;

// --------------------
// -----Parameters-----
// --------------------
float angular_resolution = 0.5f;
float support_size = 0.2f;
pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
bool setUnseenToMaxRange = false;

// --------------
// -----Help-----
// --------------
void 
printUsage (const char* progName)

  std::cout << "\\n\\nUsage: "<<progName<<" [options] <scene.pcd>\\n\\n"
            << "Options:\\n"
            << "-------------------------------------------\\n"
            << "-r <float>   angular resolution in degrees (default "<<angular_resolution<<")\\n"
            << "-c <int>     coordinate frame (default "<< (int)coordinate_frame<<")\\n"
            << "-m           Treat all unseen points as maximum range readings\\n"
            << "-s <float>   support size for the interest points (diameter of the used sphere - "
            <<                                                     "default "<<support_size<<")\\n"
            << "-h           this help\\n"
            << "\\n\\n";


//void 
//setViewerPose (pcl::visualization::PCLVisualizer& viewer, const Eigen::Affine3f& viewer_pose)
//
  //Eigen::Vector3f pos_vector = viewer_pose * Eigen::Vector3f (0, 0, 0);
  //Eigen::Vector3f look_at_vector = viewer_pose.rotation () * Eigen::Vector3f (0, 0, 1) + pos_vector;
  //Eigen::Vector3f up_vector = viewer_pose.rotation () * Eigen::Vector3f (0, -1, 0);
  //viewer.setCameraPosition (pos_vector[0], pos_vector[1], pos_vector[2],
                            //look_at_vector[0], look_at_vector[1], look_at_vector[2],
                            //up_vector[0], up_vector[1], up_vector[2]);
//

// --------------
// -----Main-----
// --------------
int 
main (int argc, char** argv)

  // --------------------------------------
  // -----Parse Command Line Arguments-----
  // --------------------------------------
  if (pcl::console::find_argument (argc, argv, "-h") >= 0)
  
    printUsage (argv[0]);
    return 0;
  
  if (pcl::console::find_argument (argc, argv, "-m") >= 0)
  
    setUnseenToMaxRange = true;
    std::cout << "Setting unseen values in range image to maximum range readings.\\n";
  
  int tmp_coordinate_frame;
  if (pcl::console::parse (argc, argv, "-c", tmp_coordinate_frame) >= 0)
  
    coordinate_frame = pcl::RangeImage::CoordinateFrame (tmp_coordinate_frame);
    std::cout << "Using coordinate frame "<< (int)coordinate_frame<<".\\n";
  
  if (pcl::console::parse (argc, argv, "-s", support_size) >= 0)
    std::cout << "Setting support size to "<<support_size<<".\\n";
  if (pcl::console::parse (argc, argv, "-r", angular_resolution) >= 0)
    std::cout << "Setting angular resolution to "<<angular_resolution<<"deg.\\n";
  angular_resolution = pcl::deg2rad (angular_resolution);
  
  // ------------------------------------------------------------------
  // -----Read pcd file or create example point cloud if not given-----
  // ------------------------------------------------------------------
  pcl::PointCloud<PointType>::Ptr point_cloud_ptr (new pcl::PointCloud<PointType>);
  pcl::PointCloud<PointType>& point_cloud = *point_cloud_ptr;
  pcl::PointCloud<pcl::PointWithViewpoint> far_ranges;
  Eigen::Affine3f scene_sensor_pose (Eigen::Affine3f::Identity ());
  std::vector<int> pcd_filename_indices = pcl::console::parse_file_extension_argument (argc, argv, "pcd");
  if (!pcd_filename_indices.empty ())
  
    std::string filename = argv[pcd_filename_indices[0]];
    if (pcl::io::loadPCDFile (filename, point_cloud) == -1)
    
      std::cerr << "Was not able to open file \\""<<filename<<"\\".\\n";
      printUsage (argv[0]);
      return 0;
    
    scene_sensor_pose = Eigen::Affine3f (Eigen::Translation3f (point_cloud.sensor_origin_[0],
                                                               point_cloud.sensor_origin_[1],
                                                               point_cloud.sensor_origin_[2])) *
                        Eigen::Affine3f (point_cloud.sensor_orientation_);
    std::string far_ranges_filename = pcl::getFilenameWithoutExtension (filename)+"_far_ranges.pcd";
    if (pcl::io::loadPCDFile (far_ranges_filename.c_str (), far_ranges) == -1)
      std::cout << "Far ranges file \\""<<far_ranges_filename<<"\\" does not exists.\\n";
  
  else
  
    setUnseenToMaxRange = true;
    std::cout << "\\nNo *.pcd file given => Generating example point cloud.\\n\\n";
    for (float x=-0.5f; x<=0.5f; x+=0.01f)
    
      for (float y=-0.5f; y<=0.5f; y+=0.01f)
      
        PointType point;  point.x = x;  point.y = y;  point.z = 2.0f - y;
        point_cloud.push_back (point);
      
    
    point_cloud.width = point_cloud.size ();  point_cloud.height = 1;
  
  
  // -----------------------------------------------
  // -----Create RangeImage from the PointCloud-----
  // -----------------------------------------------
  float noise_level = 0.0;
  float min_range = 0.0f;
  int border_size = 1;
  pcl::RangeImage::Ptr range_image_ptr (new pcl::RangeImage);
  pcl::RangeImage& range_image = *range_image_ptr;   
  range_image.createFromPointCloud (point_cloud, angular_resolution, pcl::deg2rad (360.0f), pcl::deg2rad (180.0f),
                                   scene_sensor_pose, coordinate_frame, noise_level, min_range, border_size);
  range_image.integrateFarRanges (far_ranges);
  if (setUnseenToMaxRange)
    range_image.setUnseenToMaxRange ();
  
  // --------------------------------------------
  // -----Open 3D viewer and add point cloud-----
  // --------------------------------------------
  pcl::visualization::PCLVisualizer viewer ("3D Viewer");
  viewer.setBackgroundColor (1, 1, 1);
  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointWithRange> range_image_color_handler (range_image_ptr, 0, 0, 0);
  viewer.addPointCloud (range_image_ptr, range_image_color_handler, "range image");
  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 1, "range image");
  //viewer.addCoordinateSystem (1.0f, "global");
  //PointCloudColorHandlerCustom<PointType> point_cloud_color_handler (point_cloud_ptr, 150, 150, 150);
  //viewer.addPointCloud (point_cloud_ptr, point_cloud_color_handler, "original point cloud");
  viewer.initCameraParameters ();
  //setViewerPose (viewer, range_image.getTransformationToWorldSystem ());
  
  // --------------------------
  // -----Show range image-----
  // --------------------------
  pcl::visualization::RangeImageVisualizer range_image_widget ("Range image");
  range_image_widget.showRangeImage (range_image);
  
  // --------------------------------
  // -----Extract NARF keypoints-----
  // --------------------------------
  pcl::RangeImageBorderExtractor range_image_border_extractor;
  pcl::NarfKeypoint narf_keypoint_detector (&range_image_border_extractor);
  narf_keypoint_detector.setRangeImage (&range_image);
  narf_keypoint_detector.getParameters ().support_size = support_size;
  //narf_keypoint_detector.getParameters ().add_points_on_straight_edges = true;
  //narf_keypoint_detector.getParameters ().distance_for_additional_points = 0.5;
  
  pcl::PointCloud<int> keypoint_indices;
  narf_keypoint_detector.compute (keypoint_indices);
  std::cout << "Found "<<keypoint_indices.size ()<<" key points.\\n";

  // ----------------------------------------------
  // -----Show keypoints in range image widget-----
  // ----------------------------------------------
  //for (std::size_t i=0; i<keypoint_indices.size (); ++i)
    //range_image_widget.markPoint (keypoint_indices[i]%range_image.width,
                                  //keypoint_indices[i]/range_image.width);
  
  // -------------------------------------
  // -----Show keypoints in 3D viewer-----
  // -------------------------------------
  pcl::PointCloud<pcl::PointXYZ>::Ptr keypoints_ptr (new pcl::PointCloud<pcl::PointXYZ>);
  pcl::PointCloud<pcl::PointXYZ>& keypoints = *keypoints_ptr;
  keypoints.resize (keypoint_indices.size ());
  for (std::size_t i=0; i<keypoint_indices.size (); ++i)
    keypoints[i].getVector3fMap () = range_image[keypoint_indices[i]].getVector3fMap ();

  pcl::visualization::PointCloudColorHandlerCustom<pcl::PointXYZ> keypoints_color_handler (keypoints_ptr, 0, 255, 0);
  viewer.addPointCloud<pcl::PointXYZ> (keypoints_ptr, keypoints_color_handler, "keypoints");
  viewer.setPointCloudRenderingProperties (pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 7, "keypoints");
  
  //--------------------
  // -----Main loop-----
  //--------------------
  while (!viewer.wasStopped ())
  
    range_image_widget.spinOnce ();  // process GUI events
    viewer.spinOnce ();
    pcl_sleep(0.01);
  

2、准备CMakeLists.txt

cmake_minimum_required(VERSION 3.5 FATAL_ERROR)

project(narf)

find_package(PCL 1.2 REQUIRED)

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

add_executable (narf narf.cpp)
target_link_libraries (narf $PCL_LIBRARIES)

3、生成sln工程，准备编译，

 

4、准备执行narf.exe文件，不用添加参数

        过一会，可以发现有6个关键点，

         也就是上面图形中绿色的部分，当然RangeImage还是少不了的。