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 * $Id$ 00037 * 00038 */ 00039 00040 #include <iostream> 00041 00042 #include <pcl/io/pcd_io.h> 00043 #include <pcl/point_types.h> 00044 #include <pcl/features/normal_3d.h> 00045 #include <pcl/kdtree/kdtree_flann.h> 00046 00047 int 00048 main (int, char** argv) 00049 { 00050 std::string filename = argv[1]; 00051 std::cout << "Reading " << filename << std::endl; 00052 00053 pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>); 00054 00055 if (pcl::io::loadPCDFile<pcl::PointXYZ> (filename, *cloud) == -1) // load the file 00056 { 00057 PCL_ERROR ("Couldn't read file"); 00058 return -1; 00059 } 00060 00061 std::cout << "points: " << cloud->points.size () << std::endl; 00062 00063 // Create the normal estimation class, and pass the input dataset to it 00064 pcl::NormalEstimation<pcl::PointXYZ, pcl::Normal> normal_estimation; 00065 normal_estimation.setInputCloud (cloud); 00066 00067 // Create an empty kdtree representation, and pass it to the normal estimation object. 00068 // Its content will be filled inside the object, based on the given input dataset (as no other search surface is given). 00069 pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>); 00070 normal_estimation.setSearchMethod (tree); 00071 00072 // Output datasets 00073 pcl::PointCloud<pcl::Normal>::Ptr cloud_normals (new pcl::PointCloud<pcl::Normal>); 00074 00075 // Use all neighbors in a sphere of radius 3cm 00076 normal_estimation.setRadiusSearch (0.03); 00077 00078 // Compute the features 00079 normal_estimation.compute (*cloud_normals); 00080 00081 // cloud_normals->points.size () should have the same size as the input cloud->points.size () 00082 std::cout << "cloud_normals->points.size (): " << cloud_normals->points.size () << std::endl; 00083 return 0; 00084 }