1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
|
#include <pcl/point_cloud.h>
#include <pcl/octree/octree.h>
#include <iostream>
#include <vector>
#include <ctime>
int
main (int argc, char** argv)
{
srand ((unsigned int) time (NULL));
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
// Generate pointcloud data
cloud->width = 1000;
cloud->height = 1;
cloud->points.resize (cloud->width * cloud->height);
for (size_t i = 0; i < cloud->points.size (); ++i)
{
cloud->points[i].x = 1024.0f * rand () / (RAND_MAX + 1.0f);
cloud->points[i].y = 1024.0f * rand () / (RAND_MAX + 1.0f);
cloud->points[i].z = 1024.0f * rand () / (RAND_MAX + 1.0f);
}
float resolution = 128.0f;
pcl::octree::OctreePointCloudSearch<pcl::PointXYZ> octree (resolution);
octree.setInputCloud (cloud);
octree.addPointsFromInputCloud ();
pcl::PointXYZ searchPoint;
searchPoint.x = 1024.0f * rand () / (RAND_MAX + 1.0f);
searchPoint.y = 1024.0f * rand () / (RAND_MAX + 1.0f);
searchPoint.z = 1024.0f * rand () / (RAND_MAX + 1.0f);
// Neighbors within voxel search
std::vector<int> pointIdxVec;
if (octree.voxelSearch (searchPoint, pointIdxVec))
{
std::cout << "Neighbors within voxel search at (" << searchPoint.x
<< " " << searchPoint.y
<< " " << searchPoint.z << ")"
<< std::endl;
for (size_t i = 0; i < pointIdxVec.size (); ++i)
std::cout << " " << cloud->points[pointIdxVec[i]].x
<< " " << cloud->points[pointIdxVec[i]].y
<< " " << cloud->points[pointIdxVec[i]].z << std::endl;
}
// K nearest neighbor search
int K = 10;
std::vector<int> pointIdxNKNSearch;
std::vector<float> pointNKNSquaredDistance;
std::cout << "K nearest neighbor search at (" << searchPoint.x
<< " " << searchPoint.y
<< " " << searchPoint.z
<< ") with K=" << K << std::endl;
if (octree.nearestKSearch (searchPoint, K, pointIdxNKNSearch, pointNKNSquaredDistance) > 0)
{
for (size_t i = 0; i < pointIdxNKNSearch.size (); ++i)
std::cout << " " << cloud->points[ pointIdxNKNSearch[i] ].x
<< " " << cloud->points[ pointIdxNKNSearch[i] ].y
<< " " << cloud->points[ pointIdxNKNSearch[i] ].z
<< " (squared distance: " << pointNKNSquaredDistance[i] << ")" << std::endl;
}
// Neighbors within radius search
std::vector<int> pointIdxRadiusSearch;
std::vector<float> pointRadiusSquaredDistance;
float radius = 256.0f * rand () / (RAND_MAX + 1.0f);
std::cout << "Neighbors within radius search at (" << searchPoint.x
<< " " << searchPoint.y
<< " " << searchPoint.z
<< ") with radius=" << radius << std::endl;
if (octree.radiusSearch (searchPoint, radius, pointIdxRadiusSearch, pointRadiusSquaredDistance) > 0)
{
for (size_t i = 0; i < pointIdxRadiusSearch.size (); ++i)
std::cout << " " << cloud->points[ pointIdxRadiusSearch[i] ].x
<< " " << cloud->points[ pointIdxRadiusSearch[i] ].y
<< " " << cloud->points[ pointIdxRadiusSearch[i] ].z
<< " (squared distance: " << pointRadiusSquaredDistance[i] << ")" << std::endl;
}
}
|