PCL:从深度图（pcd文件）中提取NARF关键点

 NARF(Normal Aligned Radial Feature)关键点是为了从深度图像中识别物体而提出的，对NARF关键点的提取过程有以下要求：  a) 提取的过程考虑边缘以及物体表面变化信息在内；b)在不同视角关键点可以被重复探测；c)关键点所在位置有足够的支持区域，可以计算描述子和进行唯一的估计法向量。  其对应的探测步骤如下：  (1) 遍历每个深度图像点，通过寻找在近邻区域有深度变化的位置进行边缘检测。  (2) 遍历每个深度图像点，根据近邻区域的表面变化决定一测度表面变化的系数，及变化的主方向。  (3) 根据step(2)找到的主方向计算兴趣点，表征该方向和其他方向的不同，以及该处表面的变化情况，即该点有多稳定。  (4) 对兴趣值进行平滑滤波。  (5) 进行无最大值压缩找到的最终关键点，即为NARF关键点。

#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 PointType;float angular_resolution = 0.5f; float support_size = 0.2f;pcl::RangeImage::CoordinateFrame coordinate_frame = pcl::RangeImage::CAMERA_FRAME;bool setUnseenToMaxRange = false;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";}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;      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);      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);    // ------------------------------------------------------------------    // -----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)      {    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;    }    // -----------------------------------------------    // -----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, 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.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);    }    return 0;}

结果如下，小伙伴们可自行尝试