test_invariants_estimation.cpp

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#include <gtest/gtest.h>
#include <pcl/point_cloud.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/moment_invariants.h>

using namespace pcl;
using namespace pcl::io;
using namespace std;

typedef search::KdTree<PointXYZ>::Ptr KdTreePtr;

PointCloud<PointXYZ> cloud;
vector<int> indices;
KdTreePtr tree;

TEST (PCL, MomentInvariantsEstimation)
{
  float j1, j2, j3;

  MomentInvariantsEstimation<PointXYZ, MomentInvariants> mi;

  // computePointMomentInvariants (indices))
  mi.computePointMomentInvariants (cloud, indices, j1, j2, j3);
  EXPECT_NEAR (j1, 1.59244, 1e-4);
  EXPECT_NEAR (j2, 0.652063, 1e-4);
  EXPECT_NEAR (j3, 0.053917, 1e-4);

  // computePointMomentInvariants
  mi.computePointMomentInvariants (cloud, indices, j1, j2, j3);
  EXPECT_NEAR (j1, 1.59244, 1e-4);
  EXPECT_NEAR (j2, 0.652063, 1e-4);
  EXPECT_NEAR (j3, 0.053917, 1e-4);

  // Object
  PointCloud<MomentInvariants>::Ptr moments (new PointCloud<MomentInvariants> ());

  // set parameters
  mi.setInputCloud (cloud.makeShared ());
  boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
  mi.setIndices (indicesptr);
  mi.setSearchMethod (tree);
  mi.setKSearch (static_cast<int> (indices.size ()));

  // estimate
  mi.compute (*moments);
  EXPECT_EQ (moments->points.size (), indices.size ());

  for (size_t i = 0; i < moments->points.size (); ++i)
  {
    EXPECT_NEAR (moments->points[i].j1, 1.59244, 1e-4);
    EXPECT_NEAR (moments->points[i].j2, 0.652063, 1e-4);
    EXPECT_NEAR (moments->points[i].j3, 0.053917, 1e-4);
  }
}

#ifndef PCL_ONLY_CORE_POINT_TYPES

  TEST (PCL, MomentInvariantsEstimationEigen)
  {
    float j1, j2, j3;

    MomentInvariantsEstimation<PointXYZ, Eigen::MatrixXf> mi;

    // computePointMomentInvariants (indices))
    mi.computePointMomentInvariants (cloud, indices, j1, j2, j3);
    EXPECT_NEAR (j1, 1.59244, 1e-4);
    EXPECT_NEAR (j2, 0.652063, 1e-4);
    EXPECT_NEAR (j3, 0.053917, 1e-4);

    // computePointMomentInvariants
    mi.computePointMomentInvariants (cloud, indices, j1, j2, j3);
    EXPECT_NEAR (j1, 1.59244, 1e-4);
    EXPECT_NEAR (j2, 0.652063, 1e-4);
    EXPECT_NEAR (j3, 0.053917, 1e-4);

    // Object
    PointCloud<Eigen::MatrixXf>::Ptr moments (new PointCloud<Eigen::MatrixXf>);

    // set parameters
    mi.setInputCloud (cloud.makeShared ());
    boost::shared_ptr<vector<int> > indicesptr (new vector<int> (indices));
    mi.setIndices (indicesptr);
    mi.setSearchMethod (tree);
    mi.setKSearch (static_cast<int> (indices.size ()));

    // estimate
    mi.computeEigen (*moments);
    EXPECT_EQ (moments->points.rows (), indices.size ());

    for (int i = 0; i < moments->points.rows (); ++i)
    {
      EXPECT_NEAR (moments->points (i, 0), 1.59244, 1e-4);
      EXPECT_NEAR (moments->points (i, 1), 0.652063, 1e-4);
      EXPECT_NEAR (moments->points (i, 2), 0.053917, 1e-4);
    }
  }
#endif


/* ---[ */
int
main (int argc, char** argv)
{
  if (argc < 2)
  {
    std::cerr << "No test file given. Please download `bun0.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  if (loadPCDFile<PointXYZ> (argv[1], cloud) < 0)
  {
    std::cerr << "Failed to read test file. Please download `bun0.pcd` and pass its path to the test." << std::endl;
    return (-1);
  }

  indices.resize (cloud.points.size ());
  for (int i = 0; i < static_cast<int> (indices.size ()); ++i)
    indices[i] = i;

  tree.reset (new search::KdTree<PointXYZ> (false));
  tree->setInputCloud (cloud.makeShared ());

  testing::InitGoogleTest (&argc, argv);
  return (RUN_ALL_TESTS ());
}
/* ]--- */