example_fast_point_feature_histograms.cpp
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00001 /*
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00036  * $Id: example_fast_point_feature_histograms.cpp 4516 2012-02-17 08:03:46Z nizar $
00037  *
00038  */
00039 
00040 
00041 #include <iostream>
00042 #include <vector>
00043 
00044 #include <pcl/io/pcd_io.h>
00045 #include <pcl/point_types.h>
00046 #include <pcl/features/fpfh.h>
00047 #include <pcl/features/normal_3d.h>
00048 
00049 int
00050 main (int argc, char** argv)
00051 {
00052   if (argc < 2)
00053   {
00054     throw std::runtime_error ("Required arguments: filename.pcd");
00055   }
00056 
00057   std::string fileName = argv[1];
00058   std::cout << "Reading " << fileName << std::endl;
00059 
00060   pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
00061 
00062   if (pcl::io::loadPCDFile<pcl::PointXYZ> (fileName, *cloud) == -1) // load the file
00063   {
00064     PCL_ERROR ("Couldn't read file");
00065     return (-1);
00066   }
00067 
00068   std::cout << "Loaded " << cloud->points.size () << " points." << std::endl;
00069 
00070   // Compute the normals
00071   pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> normal_estimation;
00072   normal_estimation.setInputCloud (cloud);
00073 
00074   pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
00075   normal_estimation.setSearchMethod (tree);
00076 
00077   pcl::PointCloud<pcl::Normal>::Ptr cloud_with_normals (new pcl::PointCloud<pcl::Normal>);
00078 
00079   normal_estimation.setRadiusSearch (0.03);
00080 
00081   normal_estimation.compute (*cloud_with_normals);
00082 
00083   // Setup the feature computation
00084 
00085   pcl::FPFHEstimation<pcl::PointXYZ, pcl::Normal, pcl::FPFHSignature33> fpfh_estimation;
00086   // Provide the original point cloud (without normals)
00087   fpfh_estimation.setInputCloud (cloud);
00088   // Provide the point cloud with normals
00089   fpfh_estimation.setInputNormals (cloud_with_normals);
00090 
00091   // fpfhEstimation.setInputWithNormals(cloud, cloudWithNormals); PFHEstimation does not have this function
00092   // Use the same KdTree from the normal estimation
00093   fpfh_estimation.setSearchMethod (tree);
00094 
00095   pcl::PointCloud<pcl::FPFHSignature33>::Ptr pfh_features (new pcl::PointCloud<pcl::FPFHSignature33>);
00096 
00097   fpfh_estimation.setRadiusSearch (0.2);
00098 
00099   // Actually compute the spin images
00100   fpfh_estimation.compute (*pfh_features);
00101 
00102   std::cout << "output points.size (): " << pfh_features->points.size () << std::endl;
00103 
00104   // Display and retrieve the shape context descriptor vector for the 0th point.
00105   pcl::FPFHSignature33 descriptor = pfh_features->points[0];
00106   std::cout << descriptor << std::endl;
00107 
00108   return 0;
00109 }


pcl
Author(s): Open Perception
autogenerated on Mon Oct 6 2014 03:14:53