00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2009-2011, Willow Garage, Inc. 00006 * 00007 * All rights reserved. 00008 * 00009 * Redistribution and use in source and binary forms, with or without 00010 * modification, are permitted provided that the following conditions 00011 * are met: 00012 * 00013 * * Redistributions of source code must retain the above copyright 00014 * notice, this list of conditions and the following disclaimer. 00015 * * Redistributions in binary form must reproduce the above 00016 * copyright notice, this list of conditions and the following 00017 * disclaimer in the documentation and/or other materials provided 00018 * with the distribution. 00019 * * Neither the name of Willow Garage, Inc. nor the names of its 00020 * contributors may be used to endorse or promote products derived 00021 * from this software without specific prior written permission. 00022 * 00023 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00024 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00025 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00026 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00027 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00028 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00029 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00030 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00031 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00032 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00033 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00034 * POSSIBILITY OF SUCH DAMAGE. 00035 * 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 }