介绍:点云贪心三角化
输入pcd文件,输出vtk文件。
主要就是一下两个参数:
设置用于确定用于三角测量的最近邻的球面半径
gpt.setSearchRadius (radius);
设置最近邻距离的乘法器,得到每个点的最终搜索半径(这将使算法适应云中不同的点密度)。
gpt.setMu (mu);
代码如下:
#include <pcl/io/pcd_io.h> #include <pcl/io/vtk_io.h> #include <pcl/console/print.h> #include <pcl/console/parse.h> #include <pcl/console/time.h> #include <pcl/surface/gp3.h> using namespace pcl; using namespace pcl::io; using namespace pcl::console; double default_mu = 0.0; double default_radius = 0.0; void printHelp (int, char **argv) { print_error ("Syntax is: %s input.pcd output.vtk <options>\n", argv[0]); print_info (" where options are:\n"); print_info (" -radius X = use a radius of Xm around each point to determine the neighborhood (default: "); print_value ("%f", default_radius); print_info (")\n"); print_info (" -mu X = set the multipler of the nearest neighbor distance to obtain the final search radius (default: "); print_value ("%f", default_mu); print_info (")\n"); } bool loadCloud (const std::string &filename, PointCloud<PointNormal> &cloud) { TicToc tt; print_highlight ("Loading "); print_value ("%s ", filename.c_str ()); tt.tic (); if (loadPCDFile<PointNormal> (filename, cloud) < 0) return (false); print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%d", cloud.width * cloud.height); print_info (" points]\n"); print_info ("Available dimensions: "); print_value ("%s\n", pcl::getFieldsList (cloud).c_str ()); return (true); } void compute (const PointCloud<PointNormal>::Ptr &input, pcl::PolygonMesh &output, double mu, double radius) { // Estimate TicToc tt; tt.tic (); print_highlight (stderr, "Computing "); PointCloud<PointNormal>::Ptr cloud (new PointCloud<PointNormal> ()); for (size_t i = 0; i < input->size (); ++i) if (pcl_isfinite (input->points[i].x)) cloud->push_back (input->points[i]); cloud->width = static_cast<uint32_t> (cloud->size ()); cloud->height = 1; cloud->is_dense = true; GreedyProjectionTriangulation<PointNormal> gpt; gpt.setSearchMethod (pcl::search::KdTree<pcl::PointNormal>::Ptr (new pcl::search::KdTree<pcl::PointNormal>)); gpt.setInputCloud (cloud); gpt.setSearchRadius (radius); gpt.setMu (mu); gpt.reconstruct (output); print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%lu", output.polygons.size ()); print_info (" polygons]\n"); } void saveCloud (const std::string &filename, const pcl::PolygonMesh &output) { TicToc tt; tt.tic (); print_highlight ("Saving "); print_value ("%s ", filename.c_str ()); saveVTKFile (filename, output); print_info ("[done, "); print_value ("%g", tt.toc ()); print_info (" ms : "); print_value ("%lu", output.polygons.size ()); print_info (" polygons]\n"); } /* ---[ */ int main (int argc, char** argv) { print_info ("Perform surface triangulation using pcl::GreedyProjectionTriangulation. For more information, use: %s -h\n", argv[0]); if (argc < 3) { printHelp (argc, argv); return (-1); } // Parse the command line arguments for .pcd files std::vector<int> pcd_file_indices = parse_file_extension_argument (argc, argv, ".pcd"); if (pcd_file_indices.size () != 1) { print_error ("Need one input PCD file to continue.\n"); return (-1); } std::vector<int> vtk_file_indices = parse_file_extension_argument (argc, argv, ".vtk"); if (vtk_file_indices.size () != 1) { print_error ("Need one output VTK file to continue.\n"); return (-1); } // Command line parsing double mu = default_mu; double radius = default_radius; parse_argument (argc, argv, "-mu", mu); parse_argument (argc, argv, "-radius", radius); // Load the first file PointCloud<PointNormal>::Ptr cloud (new PointCloud<PointNormal>); if (!loadCloud (argv[pcd_file_indices[0]], *cloud)) return (-1); // Perform the surface triangulation pcl::PolygonMesh output; compute (cloud, output, mu, radius); // Save into the second file saveCloud (argv[vtk_file_indices[0]], output); }
来源:PCL官方示例