pcl--第三节关键点

简介

关键点也称为兴趣点，它是 2D 图像或 3D 点云或曲面模型上,可以通过检测标准来获取的具有稳定性、区别性的点集。从技术上来说,关键点的数量比原始点云或图像的数据量少很多，其与局部特征描述子结合组成关键点描述子。常用来构成原始数据的紧凑表示，具有代表性与描述性，从而加快后续识别、追踪等对数据的处理速度。

固而，关键点提取就成为 2D 与 3D 信息处理中不可或缺的关键技术。

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,关键点探测的重要一步是减少特征提取时的搜索空间,把重点放在重要的结构上,对 NARF 关键点提取过程有以下要求:

提取的过程必须考虑边缘以及物体表面变化信息在内;
关键点的位置必须稳定的可以被重复探测，即使换了不同的视角;
关键点所在的位置必须有稳定的支持区域,可以计算描述子和进行唯一的估计法向量。

为了满足上述要求,提出以下探测步骤来进行关键点提取:

遍历每个深度图像点,通过寻找在近区域有深度突变的位置进行边缘检测。
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,以及变化的主方向。
根据第二步找到的主方向计算兴趣值，表征该方向与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。
对兴趣值进行平滑过滤。
进行无最大值压缩找到最终的关键点，即为 NARF关键点

/* \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 getFilenameWithoutExtensiontypedef 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 eventsviewer.spinOnce();pcl_sleep(0.01);}
}

找不到那个far文件，无法运行