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segmentation_plane.cpp

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/*
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 *     copyright notice, this list of conditions and the following
 *     disclaimer in the documentation and/or other materials provided
 *     with the distribution.
 *   * Neither the name of Willow Garage, Inc. nor the names of its
 *     contributors may be used to endorse or promote products derived
 *     from this software without specific prior written permission.
 *
 *  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
 *  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
 *  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
 *  FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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 *  BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 *  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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 *
 * $Id: segmentation_plane.cpp 35524 2011-01-26 08:20:18Z rusu $
 *
 */

#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/segmentation/sac_segmentation.h"

/* ---[ */
int
  main (int argc, char** argv)
{
  pcl::PointCloud<pcl::PointXYZ> cloud;

  // Fill in the cloud data
  cloud.width  = 15;
  cloud.height = 1;
  cloud.points.resize (cloud.width * cloud.height);

  // Generate the data
  for (size_t i = 0; i < cloud.points.size (); ++i)
  {
    cloud.points[i].x = 1024 * rand () / (RAND_MAX + 1.0);
    cloud.points[i].y = 1024 * rand () / (RAND_MAX + 1.0);
    cloud.points[i].z = 1.0;
  }

  // Set a few outliers
  cloud.points[0].z = 2.0;
  cloud.points[3].z = -2.0;
  cloud.points[6].z = 4.0;

  std::cerr << "Point cloud data: " << cloud.points.size () << " points" << std::endl;
  for (size_t i = 0; i < cloud.points.size (); ++i)
    std::cerr << "    " << cloud.points[i].x << " " << cloud.points[i].y << " " << cloud.points[i].z << std::endl;

  pcl::ModelCoefficients coefficients;
  pcl::PointIndices inliers;
  // 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);

  pcl::PointCloud<pcl::PointXYZ>::Ptr cloudptr (new pcl::PointCloud<pcl::PointXYZ> (cloud));
  seg.setInputCloud (cloudptr);
  seg.segment (inliers, coefficients);

  if (inliers.indices.size () == 0)
  {
    ROS_ERROR ("Could not estimate a planar model for the given dataset.");
    return (-1);
  }

  std::cerr << "Model coefficients: " << coefficients.values[0] << " " << coefficients.values[1] << " "
                                      << coefficients.values[2] << " " << coefficients.values[3] << std::endl;

  std::cerr << "Model inliers: " << inliers.indices.size () << std::endl;
  for (size_t i = 0; i < inliers.indices.size (); ++i)
    std::cerr << inliers.indices[i] << "    " << cloud.points[inliers.indices[i]].x << " "
                                              << cloud.points[inliers.indices[i]].y << " "
                                              << cloud.points[inliers.indices[i]].z << std::endl;

  return (0);
}
/* ]--- */

---

pcl_tutorials
Author(s): Radu Bogdan Rusu, Bastian Steder
autogenerated on Fri Mar 1 16:30:11 2013