In this tutorial we will learn how to calculate a simple 2D convex hull polygon for a set of points supported by a plane.
The following video shows a demonstration of the code given below on the test dataset table_scene_mug_stereo_textured.pcd.
First, download the dataset table_scene_mug_stereo_textured.pcd and save it somewhere to disk.
Then, create a file, let’s say, convex_hull_2d.cpp in your favorite editor, and place the following inside it:
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 | #include <pcl/ModelCoefficients.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/sample_consensus/method_types.h>
#include <pcl/sample_consensus/model_types.h>
#include <pcl/filters/passthrough.h>
#include <pcl/filters/project_inliers.h>
#include <pcl/segmentation/sac_segmentation.h>
#include <pcl/surface/convex_hull.h>
int
main (int argc, char** argv)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>), cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>), cloud_projected (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PCDReader reader;
reader.read ("table_scene_mug_stereo_textured.pcd", *cloud);
// Build a filter to remove spurious NaNs
pcl::PassThrough<pcl::PointXYZ> pass;
pass.setInputCloud (cloud);
pass.setFilterFieldName ("z");
pass.setFilterLimits (0, 1.1);
pass.filter (*cloud_filtered);
std::cerr << "PointCloud after filtering has: " << cloud_filtered->points.size () << " data points." << std::endl;
pcl::ModelCoefficients::Ptr coefficients (new pcl::ModelCoefficients);
pcl::PointIndices::Ptr inliers (new pcl::PointIndices);
// Create the segmentation object
pcl::SACSegmentation<pcl::PointXYZ> seg;
// Optional
seg.setOptimizeCoefficients (true);
// Mandatory
seg.setModelType (pcl::SACMODEL_PLANE);
seg.setMethodType (pcl::SAC_RANSAC);
seg.setDistanceThreshold (0.01);
seg.setInputCloud (cloud_filtered);
seg.segment (*inliers, *coefficients);
// Project the model inliers
pcl::ProjectInliers<pcl::PointXYZ> proj;
proj.setModelType (pcl::SACMODEL_PLANE);
proj.setInputCloud (cloud_filtered);
proj.setModelCoefficients (coefficients);
proj.filter (*cloud_projected);
// Create a Convex Hull representation of the projected inliers
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_hull (new pcl::PointCloud<pcl::PointXYZ>);
pcl::ConvexHull<pcl::PointXYZ> chull;
chull.setInputCloud (cloud_projected);
chull.reconstruct (*cloud_hull);
std::cerr << "Convex hull has: " << cloud_hull->points.size () << " data points." << std::endl;
pcl::PCDWriter writer;
writer.write ("table_scene_mug_stereo_textured_hull.pcd", *cloud_hull, false);
return (0);
}
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The only interesting part is in the lines below, where the ConvexHull object gets created and the reconstruction is performed:
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_hull (new pcl::PointCloud<pcl::PointXYZ>);
pcl::ConvexHull<pcl::PointXYZ> chull;
chull.setInputCloud (cloud_projected);
chull.reconstruct (*cloud_hull);
Add the following lines to your CMakeLists.txt file:
1 2 3 4 5 6 7 8 9 10 11 12 | cmake_minimum_required(VERSION 2.8 FATAL_ERROR)
project(convex_hull_2d)
find_package(PCL 1.3 REQUIRED)
include_directories(${PCL_INCLUDE_DIRS})
link_directories(${PCL_LIBRARY_DIRS})
add_definitions(${PCL_DEFINITIONS})
add_executable (convex_hull_2d convex_hull_2d.cpp)
target_link_libraries (convex_hull_2d ${PCL_LIBRARIES})
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After you have made the executable, you can run it. Simply do:
$ ./convex_hull_2d
You will see something similar to:
PointCloud after filtering has: 139656 data points.
Convex hull has: 30 data points.