statistics.cpp

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/*
 * Copyright (c) 2008 Radu Bogdan Rusu <rusu -=- cs.tum.edu>
 *
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 *     * Redistributions of source code must retain the above copyright
 *       notice, this list of conditions and the following disclaimer.
 *     * Redistributions in binary form must reproduce the above copyright
 *       notice, this list of conditions and the following disclaimer in the
 *       documentation and/or other materials provided with the distribution.
 *
 * 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 COPYRIGHT OWNER OR CONTRIBUTORS BE
 * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 * POSSIBILITY OF SUCH DAMAGE.
 *
 * $Id: statistics.cpp 21050 2009-08-07 21:24:30Z jfaustwg $
 *
 */

#include <algorithm>
#include <cfloat>
#include <stereo_wall_detection/geometry/statistics.h>

namespace cloud_geometry
{

  namespace statistics
  {

    geometry_msgs::Point32
      computeMedian (const sensor_msgs::PointCloud& points)
    {
      geometry_msgs::Point32 median;

      // Copy the values to vectors for faster sorting
      std::vector<double> x (points.points.size ());
      std::vector<double> y (points.points.size ());
      std::vector<double> z (points.points.size ());
      for (unsigned int i = 0; i < points.points.size (); i++)
      {
        x[i] = points.points[i].x;
        y[i] = points.points[i].y;
        z[i] = points.points[i].z;
      }
      std::sort (x.begin (), x.end ());
      std::sort (y.begin (), y.end ());
      std::sort (z.begin (), z.end ());

      int mid = points.points.size () / 2;
      if (points.points.size () % 2 == 0)
      {
        median.x = (x[mid-1] + x[mid]) / 2;
        median.y = (y[mid-1] + y[mid]) / 2;
        median.z = (z[mid-1] + z[mid]) / 2;
      }
      else
      {
        median.x = x[mid];
        median.y = y[mid];
        median.z = z[mid];
      }
      return (median);
    }


    geometry_msgs::Point32
      computeMedian (const sensor_msgs::PointCloud &points, const std::vector<int> &indices)
    {
      geometry_msgs::Point32 median;

      // Copy the values to vectors for faster sorting
      std::vector<double> x (indices.size ());
      std::vector<double> y (indices.size ());
      std::vector<double> z (indices.size ());
      for (unsigned int i = 0; i < indices.size (); i++)
      {
        x[i] = points.points.at (indices.at (i)).x;
        y[i] = points.points.at (indices.at (i)).y;
        z[i] = points.points.at (indices.at (i)).z;
      }
      std::sort (x.begin (), x.end ());
      std::sort (y.begin (), y.end ());
      std::sort (z.begin (), z.end ());

      int mid = indices.size () / 2;
      if (indices.size () % 2 == 0)
      {
        median.x = (x[mid-1] + x[mid]) / 2;
        median.y = (y[mid-1] + y[mid]) / 2;
        median.z = (z[mid-1] + z[mid]) / 2;
      }
      else
      {
        median.x = x[mid];
        median.y = y[mid];
        median.z = z[mid];
      }
      return (median);
    }


    double
      computeMedianAbsoluteDeviation (const sensor_msgs::PointCloud &points, double sigma)
    {
      // median (dist (x - median (x)))
      geometry_msgs::Point32 median = computeMedian (points);

      std::vector<double> distances (points.points.size ());

      for (unsigned int i = 0; i < points.points.size (); i++)
        distances[i] = (points.points[i].x - median.x) * (points.points[i].x - median.x) +
                       (points.points[i].y - median.y) * (points.points[i].y - median.y) +
                       (points.points[i].z - median.z) * (points.points[i].z - median.z);

      std::sort (distances.begin (), distances.end ());

      double result;
      int mid = points.points.size () / 2;
      // Do we have a "middle" point or should we "estimate" one ?
      if (points.points.size () % 2 == 0)
        result = (sqrt (distances[mid-1]) + sqrt (distances[mid])) / 2;
      else
        result = sqrt (distances[mid]);
      return (sigma * result);
    }


    double
      computeMedianAbsoluteDeviation (const sensor_msgs::PointCloud &points, const std::vector<int> &indices, double sigma)
    {
      // median (dist (x - median (x)))
      geometry_msgs::Point32 median = computeMedian (points, indices);

      std::vector<double> distances (indices.size ());

      for (unsigned int i = 0; i < indices.size (); i++)
        distances[i] = (points.points.at (indices.at (i)).x - median.x) * (points.points.at (indices.at (i)).x - median.x) +
                       (points.points.at (indices.at (i)).y - median.y) * (points.points.at (indices.at (i)).y - median.y) +
                       (points.points.at (indices.at (i)).z - median.z) * (points.points.at (indices.at (i)).z - median.z);

      std::sort (distances.begin (), distances.end ());

      double result;
      int mid = indices.size () / 2;
      // Do we have a "middle" point or should we "estimate" one ?
      if (indices.size () % 2 == 0)
        result = (sqrt (distances[mid-1]) + sqrt (distances[mid])) / 2;
      else
        result = sqrt (distances[mid]);

      return (sigma * result);
    }


    void
      getChannelMeanStd (const sensor_msgs::PointCloud &points, int d_idx, double &mean, double &stddev)
    {
      double sum = 0, sq_sum = 0;

      for (unsigned int i = 0; i < points.points.size (); i++)
      {
        sum += points.channels.at (d_idx).values.at (i);
        sq_sum += points.channels.at (d_idx).values.at (i) * points.channels.at (d_idx).values.at (i);
      }
      mean = sum / points.points.size ();
      double variance = (double)(sq_sum - sum * sum / points.points.size ()) / (points.points.size () - 1);
      stddev = sqrt (variance);
    }


    void
      getChannelMeanStd (const sensor_msgs::PointCloud &points, const std::vector<int> &indices, int d_idx, double &mean, double &stddev)
    {
      double sum = 0, sq_sum = 0;

      for (unsigned int i = 0; i < indices.size (); i++)
      {
        sum += points.channels.at (d_idx).values.at (indices.at (i));
        sq_sum += points.channels.at (d_idx).values.at (indices.at (i)) * points.channels.at (d_idx).values.at (indices.at (i));
      }
      mean = sum / indices.size ();
      double variance = (double)(sq_sum - sum * sum / indices.size ()) / (indices.size () - 1);
      stddev = sqrt (variance);
    }


    void
      selectPointsOutsideDistribution (const sensor_msgs::PointCloud &points, const std::vector<int> &indices, int d_idx,
                                       double mean, double stddev, double alpha, std::vector<int> &inliers)
    {
      inliers.resize (indices.size ());
      int nr_i = 0;
      for (unsigned int i = 0; i < indices.size (); i++)
      {
        if ( (points.channels.at (d_idx).values.at (indices.at (i)) > (mean + alpha * stddev)) ||
             (points.channels.at (d_idx).values.at (indices.at (i)) < (mean - alpha * stddev))
           )
        {
          inliers[nr_i] = indices.at (i);
          nr_i++;
        }
      }
      inliers.resize (nr_i);
    }


    void
      selectPointsInsideDistribution (const sensor_msgs::PointCloud &points, const std::vector<int> &indices, int d_idx,
                                      double mean, double stddev, double alpha, std::vector<int> &inliers)
    {
      inliers.resize (indices.size ());
      int nr_i = 0;
      for (unsigned int i = 0; i < indices.size (); i++)
      {
        if ( (points.channels.at (d_idx).values.at (indices.at (i)) < (mean + alpha * stddev)) &&
             (points.channels.at (d_idx).values.at (indices.at (i)) > (mean - alpha * stddev))
           )
        {
          inliers[nr_i] = indices.at (i);
          nr_i++;
        }
      }
      inliers.resize (nr_i);
    }


    void
      getTrimean (std::vector<int> values, double &trimean)
    {
      nth_element (values.begin (), values.begin () + (int)(values.size () * 0.25), values.end ());
      int p_25 = *(values.begin () + (int)(values.size () * 0.25));

      nth_element (values.begin (), values.begin () + (int)(values.size () * 0.5), values.end ());
      int p_50 = *(values.begin () + (int)(values.size () * 0.5));

      nth_element (values.begin (), values.begin () + (int)(values.size () * 0.75), values.end ());
      int p_75 = *(values.begin () + (int)(values.size () * 0.75));

      trimean = (p_25 + 2.0 * p_50 + p_75) / 4.0;
    }

  }
}

---

stereo_wall_detection
Author(s): Radu Bogdan Rusu
autogenerated on Fri Jan 11 09:37:14 2013