PCL点特征描述与提取

1、NARF_Feature_Extraction

cpp

 /* \author Bastian Steder */
 #include <iostream>
 #include <boost/thread/thread.hpp>
 #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/features/narf_descriptor.h>
 #include <pcl/console/parse.h>

 #include "vtkImageViewer.h"
 #include "vtkInteractionImageModule.h"
 #include "vtkInteractionWidgetsModule.h"
 typedef pcl::PointXYZ PointType;
 // -----参数-----
 // --------------------
 float angular_resolution = 0.5f;
 float support_size = 0.2f;
 pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;
 bool setUnseenToMaxRange = false;
 bool rotation_invariant = true;

 // -----帮助-----
 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 to max range\n"
             << "-s <float>   support size for the interest points (diameter of the used sphere - "
                                                                   "default "<<support_size<<")\n"
             << "-o <0/1>     switch rotational invariant version of the feature on/off"
             <<               " (default "<< (int)rotation_invariant<<")\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.camera_.pos[0] = pos_vector[0];
 //  viewer.camera_.pos[1] = pos_vector[1];
 //  viewer.camera_.pos[2] = pos_vector[2];
 //  viewer.camera_.focal[0] = look_at_vector[0];
 //  viewer.camera_.focal[1] = look_at_vector[1];
 //  viewer.camera_.focal[2] = look_at_vector[2];
 //  viewer.camera_.view[0] = up_vector[0];
 //  viewer.camera_.view[1] = up_vector[1];
 //  viewer.camera_.view[2] = up_vector[2];
 //  viewer.updateCamera ();
 //}
 // -----主函数-----
 // --------------
 int
 main (int argc, char** argv)
 {
   // -----解析命令行参数-----
   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;
     cout << "Setting unseen values in range image to maximum range readings.\n";
   }
   if (pcl::console::parse (argc, argv, "-o", rotation_invariant) >= 0)
     cout << "Switching rotation invariant feature version "<< (rotation_invariant ? "on" : "off")<<".\n";
   int tmp_coordinate_frame;
   if (pcl::console::parse (argc, argv, "-c", tmp_coordinate_frame) >= 0)
   {
     coordinate_frame = pcl::RangeImage::CoordinateFrame (tmp_coordinate_frame);
     cout << "Using coordinate frame "<< (int)coordinate_frame<<".\n";
   }
   if (pcl::console::parse (argc, argv, "-s", support_size) >= 0)
     cout << "Setting support size to "<<support_size<<".\n";
   if (pcl::console::parse (argc, argv, "-r", angular_resolution) >= 0)
     cout << "Setting angular resolution to "<<angular_resolution<<"deg.\n";
   angular_resolution = pcl::deg2rad (angular_resolution);
 // -----读取pcd文件，或者如果没有给出，则创建一个样本点云-----
   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)
     {
       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;
     cout << "\nNo *.pcd file given => Genarating 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.points.push_back (point);
       }
     }
     point_cloud.width = (int) point_cloud.points.size ();  point_cloud.height = 1;
   }
  // -----从点云中创建深度图像----
 float noise_level = 0.0;
   float min_range = 0.0f;
   int border_size = 1;
   boost::shared_ptr<pcl::RangeImage> 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 ();

   // -----打开三维观察仪并加入点云-----
   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.initCameraParameters ();
  // setViewerPose (viewer, range_image.getTransformationToWorldSystem ());
   // -----显示深度图像-----
   pcl::visualization::RangeImageVisualizer  range_image_widget ("Range image");
   range_image_widget.showRangeImage (range_image);
   // -----提取 NARF 关键点-----
   pcl::RangeImageBorderExtractor range_image_border_extractor;
   pcl::NarfKeypoint narf_keypoint_detector;
   narf_keypoint_detector.setRangeImageBorderExtractor (&range_image_border_extractor);
   narf_keypoint_detector.setRangeImage (&range_image);
   narf_keypoint_detector.getParameters ().support_size = support_size;

   pcl::PointCloud<int> keypoint_indices;
   narf_keypoint_detector.compute (keypoint_indices);
   std::cout << "Found "<<keypoint_indices.points.size ()<<" key points.\n";
   // -----在深度图像窗口显示关键点-----
   //for (size_t i=0; i<keypoint_indices.points.size (); ++i)
     //range_image_widget.markPoint (keypoint_indices.points[i]%range_image.width,
                                   //keypoint_indices.points[i]/range_image.width);
 // -----在三维视图中显示关键点 -----
     pcl::PointCloud<pcl::PointXYZ>::Ptr keypoints_ptr (new pcl::PointCloud<pcl::PointXYZ>);
   pcl::PointCloud<pcl::PointXYZ>& keypoints = *keypoints_ptr;
   keypoints.points.resize (keypoint_indices.points.size ());
   for (size_t i=0; i<keypoint_indices.points.size (); ++i)
     keypoints.points[i].getVector3fMap () = range_image.points[keypoint_indices.points[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");
   // -----为特征点提取NARF描述子-----
   std::vector<int> keypoint_indices2;
   keypoint_indices2.resize (keypoint_indices.points.size ());
   for (unsigned int i=0; i<keypoint_indices.size (); ++i)
 //要得到正确的向量类型，这一步是必要的
     keypoint_indices2[i]=keypoint_indices.points[i];
   pcl::NarfDescriptor narf_descriptor (&range_image, &keypoint_indices2);
   narf_descriptor.getParameters ().support_size = support_size;
   narf_descriptor.getParameters ().rotation_invariant = rotation_invariant;
   pcl::PointCloud<pcl::Narf36> narf_descriptors;
   narf_descriptor.compute (narf_descriptors);
   cout << "Extracted "<<narf_descriptors.size ()<<" descriptors for "
                       <<keypoint_indices.points.size ()<< " keypoints.\n";
   // -----Main loop-----
   while (!viewer.wasStopped ())
   {
 range_image_widget.spinOnce ();
 //处理用户交互事件
     viewer.spinOnce ();
     pcl_sleep(0.01);
   }
 }

运行：

2、NARF_Keypoint_Extraction

可以移植到Qt中，注意变量设置和参数定义，读取文件时保持与成员变量一致，后面的循环可以丢掉。

配置的时候可能会提示缺少下面的头文件，找到头文件，加上去即可：

 #include "vtkImageViewer.h"
 #include "vtkInteractionImageModule.h"
 #include "vtkInteractionWidgetsModule.h"

narf_keypoint_extraction.cpp:

 #include <iostream>

 #include <boost/thread/thread.hpp>
 #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>

 typedef pcl::PointXYZ PointT_XYZ;

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


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

         setUnseenToMaxRange = true;
         cout << "Setting unseen values in range image to maximum range readings.\n";


     angular_resolution = pcl::deg2rad(angular_resolution);

     // ------------------------------------------------------------------
     // -----Read pcd file or create example point cloud if not given-----
     // ------------------------------------------------------------------
     pcl::PointCloud<PointT_XYZ>::Ptr cloud(new pcl::PointCloud<PointT_XYZ>);
     pcl::PointCloud<PointT_XYZ>& point_cloud = *cloud;
     pcl::PointCloud<pcl::PointWithViewpoint> far_ranges;
     Eigen::Affine3f scene_sensor_pose(Eigen::Affine3f::Identity());

     pcl::io::loadPCDFile("frame_00000.pcd", point_cloud);//frame_00000//bunny


     // -----------------------------------------------
     // -----Create RangeImage from the PointCloud-----
     // -----------------------------------------------
     float noise_level = 0.0;
     float min_range = 0.0f;
     int border_size = 1;
     boost::shared_ptr<pcl::RangeImage> 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, 0.5, 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<PointT_XYZ> point_cloud_color_handler (cloud, 150, 150, 150);
     //viewer.addPointCloud (cloud, 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.points.size() << " key points.\n";

     // ----------------------------------------------
     // -----Show keypoints in range image widget-----
     // ----------------------------------------------
     //for (size_t i=0; i<keypoint_indices.points.size (); ++i)
     //range_image_widget.markPoint (keypoint_indices.points[i]%range_image.width,
     //keypoint_indices.points[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.points.resize(keypoint_indices.points.size());
     for (size_t i = 0; i < keypoint_indices.points.size(); ++i)
         keypoints.points[i].getVector3fMap() = range_image.points[keypoint_indices.points[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);
     }
 }