Thirteenth chapter

Signed-off-by: Hao Guo <[email protected]>

第十三章/1 resampling/source/CMakeLists.txt

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+cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
+project(resampling)
+find_package(PCL 1.2 REQUIRED)
+include_directories(${PCL_INCLUDE_DIRS})
+link_directories(${PCL_LIBRARY_DIRS})
+add_definitions(${PCL_DEFINITIONS})
+add_executable (resampling resampling.cpp)
+target_link_libraries (resampling ${PCL_LIBRARIES})

第十三章/1 resampling/source/resampling.cpp

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+#include <pcl/point_types.h>
+#include <pcl/io/pcd_io.h>
+#include <pcl/kdtree/kdtree_flann.h>
+#include <pcl/surface/mls.h>
+int
+main (int argc, char** argv)
+{// 将一个适当类型的输入文件加载到对象PointCloud中
+ pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ> ());
+ // 加载bun0.pcd文件，加载的文件在 PCL的测试数据中是存在的 
+ pcl::io::loadPCDFile ("table_scene_lms400_downsampled.pcd", *cloud);
+ // 创建一个KD树
+ pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+ // 输出文件中有PointNormal类型，用来存储移动最小二乘法算出的法线
+ pcl::PointCloud<pcl::PointNormal> mls_points;
+ // 定义对象 (第二种定义类型是为了存储法线, 即使用不到也需要定义出来)
+ pcl::MovingLeastSquares<pcl::PointXYZ, pcl::PointNormal> mls;
+ mls.setComputeNormals (true);
+ //设置参数
+ mls.setInputCloud (cloud);
+ mls.setPolynomialFit (true);
+ mls.setSearchMethod (tree);
+ mls.setSearchRadius (0.03);
+ // 曲面重建
+ mls.process (mls_points);
+ // 保存结果
+ pcl::io::savePCDFile ("bun0-mls.pcd", mls_points);
+} 

第十三章/2 concave_hull_2d/source/CMakeLists.txt

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+cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
+
+project(concave_hull_2d)
+
+find_package(PCL 1.2 REQUIRED)
+
+include_directories(${PCL_INCLUDE_DIRS})
+link_directories(${PCL_LIBRARY_DIRS})
+add_definitions(${PCL_DEFINITIONS})
+
+add_executable (concave_hull_2d concave_hull_2d.cpp)
+target_link_libraries (concave_hull_2d ${PCL_LIBRARIES})

第十三章/2 concave_hull_2d/source/concave_hull_2d.cpp

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+#include <pcl/ModelCoefficients.h>
+#include <pcl/io/pcd_io.h>
+#include <pcl/point_types.h>
+#include <pcl/sample_consensus/method_types.h>
+#include <pcl/sample_consensus/model_types.h>
+#include <pcl/filters/passthrough.h>
+#include <pcl/filters/project_inliers.h>
+#include <pcl/segmentation/sac_segmentation.h>
+#include <pcl/surface/concave_hull.h>
+
+int
+main (int argc, char** argv)
+{
+ pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>), 
+ cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), 
+ cloud_projected (new pcl::PointCloud<pcl::PointXYZ>);
+ pcl::PCDReader reader;
+
+ reader.read ("table_scene_mug_stereo_textured.pcd", *cloud);
+ // Build a filter to remove spurious NaNs
+ pcl::PassThrough<pcl::PointXYZ> pass;
+ pass.setInputCloud (cloud);
+ pass.setFilterFieldName ("z");
+ pass.setFilterLimits (0, 1.1);
+ pass.filter (*cloud_filtered);
+ std::cerr << "PointCloud after filtering has: "
+ << cloud_filtered->points.size () << " data points." << std::endl;
+
+ pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
+ pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
+ // Create the segmentation object
+ pcl::SACSegmentation<pcl::PointXYZ> seg;
+ // Optional
+ seg.setOptimizeCoefficients (true);
+ // Mandatory
+ seg.setModelType (pcl::SACMODEL_PLANE);
+ seg.setMethodType (pcl::SAC_RANSAC);
+ seg.setDistanceThreshold (0.01);
+
+ seg.setInputCloud (cloud_filtered);
+ seg.segment (*inliers, *coefficients);
+ std::cerr << "PointCloud after segmentation has: "
+ << inliers->indices.size () << " inliers." << std::endl;
+
+ // Project the model inliers
+ pcl::ProjectInliers<pcl::PointXYZ> proj;
+ proj.setModelType (pcl::SACMODEL_PLANE);
+ proj.setInputCloud (cloud_filtered);
+ proj.setModelCoefficients (coefficients);
+ proj.filter (*cloud_projected);
+ std::cerr << "PointCloud after projection has: "
+ << cloud_projected->points.size () << " data points." << std::endl;
+
+ // Create a Concave Hull representation of the projected inliers
+ pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_hull (new pcl::PointCloud<pcl::PointXYZ>);
+ pcl::ConcaveHull<pcl::PointXYZ> chull;
+ chull.setInputCloud (cloud_projected);
+ chull.setAlpha (0.1);
+ chull.reconstruct (*cloud_hull);
+
+ std::cerr << "Concave hull has: " << cloud_hull->points.size ()
+ << " data points." << std::endl;
+
+ pcl::PCDWriter writer;
+ writer.write ("table_scene_mug_stereo_textured_hull.pcd", *cloud_hull, false);
+
+ return (0);
+}

第十三章/3 greedy_projection/source/CMakeLists.txt

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+cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
+
+project(greedy_projection)
+
+find_package(PCL 1.2 REQUIRED)
+
+include_directories(${PCL_INCLUDE_DIRS})
+link_directories(${PCL_LIBRARY_DIRS})
+add_definitions(${PCL_DEFINITIONS})
+
+add_executable (greedy_projection greedy_projection.cpp)
+target_link_libraries (greedy_projection ${PCL_LIBRARIES})

第十三章/3 greedy_projection/source/greedy_projection.cpp

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+#include <pcl/point_types.h>
+#include <pcl/io/pcd_io.h>
+#include <pcl/kdtree/kdtree_flann.h>
+#include <pcl/features/normal_3d.h>
+#include <pcl/surface/gp3.h>
+#include <pcl/visualization/pcl_visualizer.h>
+#include <boost/thread/thread.hpp>
+
+
+int
+main (int argc, char** argv)
+{
+ // Load input file into a PointCloud<T> with an appropriate type
+ pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
+ sensor_msgs::PointCloud2 cloud_blob;
+ pcl::io::loadPCDFile ("table_scene_lms400_downsampled.pcd", cloud_blob);
+ pcl::fromROSMsg (cloud_blob, *cloud);
+ //* the data should be available in cloud
+
+ // Normal estimation*
+ pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> n;
+ pcl::PointCloud<pcl::Normal>::Ptr normals (new pcl::PointCloud<pcl::Normal>);
+ pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+ tree->setInputCloud (cloud);
+ n.setInputCloud (cloud);
+ n.setSearchMethod (tree);
+ n.setKSearch (20);
+ n.compute (*normals);
+ //* normals should not contain the point normals + surface curvatures
+
+ // Concatenate the XYZ and normal fields*
+ pcl::PointCloud<pcl::PointNormal>::Ptr cloud_with_normals (new pcl::PointCloud<pcl::PointNormal>);
+ pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
+ //* cloud_with_normals = cloud + normals
+
+ // Create search tree*
+ pcl::search::KdTree<pcl::PointNormal>::Ptr tree2 (new pcl::search::KdTree<pcl::PointNormal>);
+ tree2->setInputCloud (cloud_with_normals);
+
+ // Initialize objects
+ pcl::GreedyProjectionTriangulation<pcl::PointNormal> gp3;
+ pcl::PolygonMesh triangles;
+
+ // Set the maximum distance between connected points (maximum edge length)
+ gp3.setSearchRadius (0.025);
+
+ // Set typical values for the parameters
+ gp3.setMu (2.5);
+ gp3.setMaximumNearestNeighbors (100);
+ gp3.setMaximumSurfaceAngle(M_PI/4); // 45 degrees
+ gp3.setMinimumAngle(M_PI/18); // 10 degrees
+ gp3.setMaximumAngle(2*M_PI/3); // 120 degrees
+ gp3.setNormalConsistency(false);
+
+ // Get result
+ gp3.setInputCloud (cloud_with_normals);
+ gp3.setSearchMethod (tree2);
+ gp3.reconstruct (triangles);
+ // std::cout << triangles;
+ // Additional vertex information
+ std::vector<int> parts = gp3.getPartIDs();
+ std::vector<int> states = gp3.getPointStates();
+ boost::shared_ptr<pcl::visualization::PCLVisualizer> viewer (new pcl::visualization::PCLVisualizer ("3D Viewer"));
+ viewer->setBackgroundColor (0, 0, 0);
+ viewer->addPolygonMesh(triangles,"my");
+
+ viewer->addCoordinateSystem (1.0);
+ viewer->initCameraParameters ();
+ // Ö÷Ñ­»·
+ while (!viewer->wasStopped ())
+ {
+ viewer->spinOnce (100);
+ boost::this_thread::sleep (boost::posix_time::microseconds (100000));
+ }
+ // Finish
+ return (0);
+}