example_rift_estimation.cpp
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00036  * $Id: example_rift_estimation.cpp 5172 2012-03-18 10:43:15Z desinghkar $
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00040 // STL
00041 #include <iostream>
00042 
00043 // PCL
00044 #include <pcl/io/pcd_io.h>
00045 #include <pcl/point_types.h>
00046 #include <pcl/common/io.h>
00047 #include <pcl/features/normal_3d.h>
00048 #include <pcl/kdtree/kdtree_flann.h>
00049 #include <pcl/features/rift.h>
00050 #include <pcl/features/intensity_gradient.h>
00051 
00052 int
00053 main (int, char** argv)
00054 {
00055   std::string filename = argv[1];
00056   std::cout << "Reading " << filename << std::endl;
00057 
00058   pcl::PointCloud<pcl::PointXYZI>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZI>);
00059 
00060   if (pcl::io::loadPCDFile<pcl::PointXYZI> (filename, *cloud) == -1) // load the file
00061   {
00062     PCL_ERROR ("Couldn't read file");
00063     return -1;
00064   }
00065 
00066   std::cout << "points: " << cloud->points.size () << std::endl;
00067 
00068   // Estimate the surface normals
00069   pcl::PointCloud<pcl::Normal>::Ptr cloud_n (new pcl::PointCloud<pcl::Normal>);
00070   pcl::NormalEstimation<pcl::PointXYZI, pcl::Normal> norm_est;
00071   norm_est.setInputCloud(cloud);
00072   pcl::search::KdTree<pcl::PointXYZI>::Ptr treept1 (new pcl::search::KdTree<pcl::PointXYZI> (false));
00073   norm_est.setSearchMethod(treept1);
00074   norm_est.setRadiusSearch(0.25);
00075   norm_est.compute(*cloud_n);
00076 
00077   std::cout<<" Surface normals estimated";
00078   std::cout<<" with size "<< cloud_n->points.size() <<std::endl;
00079  
00080   // Estimate the Intensity Gradient
00081   pcl::PointCloud<pcl::IntensityGradient>::Ptr cloud_ig (new pcl::PointCloud<pcl::IntensityGradient>);
00082   pcl::IntensityGradientEstimation<pcl::PointXYZI, pcl::Normal, pcl::IntensityGradient> gradient_est;
00083   gradient_est.setInputCloud(cloud);
00084   gradient_est.setInputNormals(cloud_n);
00085   pcl::search::KdTree<pcl::PointXYZI>::Ptr treept2 (new pcl::search::KdTree<pcl::PointXYZI> (false));
00086   gradient_est.setSearchMethod(treept2);
00087   gradient_est.setRadiusSearch(0.25);
00088   gradient_est.compute(*cloud_ig);
00089   std::cout<<" Intesity Gradient estimated";
00090   std::cout<<" with size "<< cloud_ig->points.size() <<std::endl;
00091 
00092 
00093   // Estimate the RIFT feature
00094   pcl::RIFTEstimation<pcl::PointXYZI, pcl::IntensityGradient, pcl::Histogram<32> > rift_est;
00095   pcl::search::KdTree<pcl::PointXYZI>::Ptr treept3 (new pcl::search::KdTree<pcl::PointXYZI> (false));
00096   rift_est.setSearchMethod(treept3);
00097   rift_est.setRadiusSearch(10.0);
00098   rift_est.setNrDistanceBins (4);
00099   rift_est.setNrGradientBins (8);
00100   rift_est.setInputCloud(cloud);
00101   rift_est.setInputGradient(cloud_ig);
00102   pcl::PointCloud<pcl::Histogram<32> > rift_output;
00103   rift_est.compute(rift_output);
00104 
00105   std::cout<<" RIFT feature estimated";
00106   std::cout<<" with size "<<rift_output.points.size()<<std::endl;
00107   
00108   // Display and retrieve the rift descriptor vector for the first point
00109   pcl::Histogram<32> first_descriptor = rift_output.points[0];
00110   std::cout << first_descriptor << std::endl;
00111   return 0;
00112 }


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