PCL从距离图像提取NARF关键点

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今天学习了PCL开源库中NARF关键点提取的相关代码,记录下来,以便后续查阅。


代码出处:


PCL官方文档

#include "stdafx.h"
#include <iostream>
#include <boost\thread\thread.hpp>
#include <pcl\range_image\range_image.h>
#include <pcl\io\pcd_io.h>
#include <pcl\visualization\pcl_visualizer.h>
#include <pcl\visualization\range_image_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"
		<< "------------------------------------"
		<< "-r <float> angular resolution in degrees(default " << angular_resolution << ")\n"
		<< "-c <int>   coordinate frame (default " << (int)coordinate_frame << ")\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;
		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);
		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;//引用
	pcl::PointCloud<pcl::PointWithViewpoint> far_ranges;
	Eigen::Affine3f scene_sensor_pose(Eigen::Affine3f::Identity());//仿射变换
	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);
	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_FONT_SIZE, 1, "range_image");
	viewer.addCoordinateSystem(1.0f, "global");
	pcl::visualization::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();
	// --------------------------
	// -----Show range image-----
	// --------------------------
	pcl::visualization::RangeImageVisualizer range_image_widget("Range image");
	range_image_widget.showRangeImage(range_image);

	// --------------------------------
	// -----Extract NARF keypoints-----
	// --------------------------------
	pcl::RangeImageBorderExtractor range_iamge_border_extractor;
	pcl::NarfKeypoint narf_keypoint_detector(&range_iamge_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;
}




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