Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Improvements to OUR-CVFH Estimation, including mapping from clusters to features and doc fixes #738

Merged
merged 1 commit into from
Jun 16, 2014
Merged

Improvements to OUR-CVFH Estimation, including mapping from clusters to features and doc fixes #738

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
15 changes: 13 additions & 2 deletions features/include/pcl/features/impl/our_cvfh.hpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -310,7 +310,7 @@ pcl::OURCVFHEstimation<PointInT, PointNT, PointOutT>::sgurf (Eigen::Vector3f & c

if ((min_axis / max_axis) > axis_ratio_)
{
PCL_WARN("Both axis are equally easy/difficult to disambiguate\n");
PCL_WARN ("Both axes are equally easy/difficult to disambiguate\n");

Eigen::Vector3f evy_copy = evy;
Eigen::Vector3f evxminus = evx * -1;
Expand Down Expand Up @@ -376,13 +376,20 @@ pcl::OURCVFHEstimation<PointInT, PointNT, PointOutT>::computeRFAndShapeDistribut
std::vector<pcl::PointIndices> & cluster_indices)
{
PointCloudOut ourcvfh_output;

cluster_axes_.clear ();
cluster_axes_.resize (centroids_dominant_orientations_.size ());

for (size_t i = 0; i < centroids_dominant_orientations_.size (); i++)
{

std::vector < Eigen::Matrix4f, Eigen::aligned_allocator<Eigen::Matrix4f> > transformations;
PointInTPtr grid (new pcl::PointCloud<PointInT>);
sgurf (centroids_dominant_orientations_[i], dominant_normals_[i], processed, transformations, grid, cluster_indices[i]);

// Make a note of how many transformations correspond to each cluster
cluster_axes_[i] = transformations.size ();

for (size_t t = 0; t < transformations.size (); t++)
{

Expand Down Expand Up @@ -512,11 +519,15 @@ pcl::OURCVFHEstimation<PointInT, PointNT, PointOutT>::computeRFAndShapeDistribut
}

ourcvfh_output.points.push_back (vfh_signature.points[0]);

ourcvfh_output.width = ourcvfh_output.points.size ();
delete[] weights;
}
}

if (ourcvfh_output.points.size ())
{
ourcvfh_output.height = 1;
}
output = ourcvfh_output;
}

Expand Down
13 changes: 12 additions & 1 deletion features/include/pcl/features/our_cvfh.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,7 @@ namespace pcl

/** \brief Creates an affine transformation from the RF axes
* \param[in] evx the x-axis
* \param[in] evy the z-axis
* \param[in] evy the y-axis
* \param[in] evz the z-axis
* \param[out] transformPC the resulting transformation
* \param[in] center_mat 4x4 matrix concatenated to the resulting transformation
Expand Down Expand Up @@ -262,6 +262,15 @@ namespace pcl
{
indices = clusters_;
}

/** \brief Gets the number of non-disambiguable axes that correspond to each centroid
* \param[out] cluster_axes vector mapping each centroid to the number of signatures
*/
inline void
getClusterAxes (std::vector<short> & cluster_axes)
{
cluster_axes = cluster_axes_;
}

/** \brief Sets the refinement factor for the clusters
* \param[in] rc the factor used to decide if a point is used to estimate a stable cluster
Expand Down Expand Up @@ -391,6 +400,8 @@ namespace pcl
std::vector<Eigen::Vector3f> dominant_normals_;
/** \brief Indices to the points representing the stable clusters */
std::vector<pcl::PointIndices> clusters_;
/** \brief Mapping from clusters to OUR-CVFH descriptors */
std::vector<short> cluster_axes_;
};
}

Expand Down