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Todo List

File file_io.h
  move this to pcl::console
Namespace openni_wrapper
  Get rid of all exception-specifications, these are useless and soon to be deprecated
Member pcl::assignNormalWeights (const PointCloud< NormalT > &cloud, index_t index, const Indices &k_indices, const std::vector< float > &k_sqr_distances)
  Currently, this function equalizes all weights to 1
Member pcl::createMapping (const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
  One could construct a pathological case where the struct has a field where the serialized data has padding
Member pcl::cuda::SampleConsensusModel< Storage >::setRadiusLimits (float min_radius, float max_radius)
  change this to set limits on the entire model
Member pcl::EuclideanClusterExtraction< PointT >::getSearchMethod () const
  fix this for a generic search tree
Class pcl::FarthestPointSampling< PointT >
  add support to export/import distance metric
Class pcl::geometry::MeshBase< DerivedT, MeshTraitsT, MeshTagT >
  Add documentation
Class pcl::geometry::MeshIO< MeshT >
  - Only writes the topology (not the mesh data).
  - Supports only ascii.
  - Does not consider the mesh traits (e.g. manifold or not)
Member pcl::gpu::EuclideanClusterExtraction< PointT >::getSearchMethod ()
  fix this for a generic search tree
Member pcl::gpu::EuclideanLabeledClusterExtraction< PointT >::extract (std::vector< PointIndices > &clusters)
  what do we do if input isn't a PointXYZ cloud?
Member pcl::gpu::EuclideanLabeledClusterExtraction< PointT >::getSearchMethod ()
  fix this for a generic search tree
Member pcl::gpu::extractEuclideanClusters (const typename pcl::PointCloud< PointT >::Ptr &host_cloud_, const pcl::gpu::Octree::Ptr &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster, unsigned int max_pts_per_cluster)
  : adjust this to a variable number settable with method
Struct pcl::gpu::people::Blob2
  : clean this out in the end, perhaps place the children in a separate struct
Member pcl::gpu::people::buildRelations (std::vector< std::vector< Blob2, Eigen::aligned_allocator< pcl::gpu::people::Blob2 > > > &sorted, PersonAttribs::Ptr person_attribs)

  This function also fixes the kinematic chain, we should implement this in a xml or LUT

  look if we can't get a more efficient implementation (iterator together with sortBlobs perhaps?)

Member pcl::gpu::people::buildRelations (std::vector< std::vector< Blob2, Eigen::aligned_allocator< pcl::gpu::people::Blob2 > > > &sorted)

  This function also fixes the kinematic chain, we should implement this in a xml or LUT

  look if we can't get a more efficient implementation (iterator together with sortBlobs perhaps?)

Member pcl::gpu::people::evaluateBlobs (Blob2 &parent, Blob2 &child, int child_nr)
  what if child is second link in stead of first link (ea forearm in stead of elbow for arm)
Member pcl::gpu::people::evaluateBlobs (Blob2 &parent, Blob2 &child, int child_nr, PersonAttribs::Ptr person_attribs)
  what if child is second link in stead of first link (ea forearm in stead of elbow for arm)
Member pcl::gpu::people::evaluateBlobVector (std::vector< std::vector< Blob2, Eigen::aligned_allocator< Blob2 > > > &sorted, unsigned int parent_label, int child_label, int child_number, PersonAttribs::Ptr person_attribs)
  once we have good evaluation function reconsider best_value
Member pcl::gpu::people::evaluateBlobVector (std::vector< std::vector< Blob2, Eigen::aligned_allocator< Blob2 > > > &sorted, unsigned int parent_label, int child_label, int child_number)
  once we have good evaluation function reconsider best_value
Member pcl::gpu::people::label_skeleton::smoothLabelImage (cv::Mat &lmap_in, cv::Mat &dmap, cv::Mat &lmap_out)

  make the patch size a parameter

  make the z-distance a parameter

  add a Gaussian contribution function to depth and vote

Member pcl::gpu::people::label_skeleton::sortIndicesToBlob2 (const pcl::PointCloud< pcl::PointXYZ > &cloud_in, unsigned int sizeThres, std::vector< std::vector< Blob2, Eigen::aligned_allocator< Blob2 > > > &sorted, std::vector< std::vector< pcl::PointIndices > > &indices)

  implement the eigenvalue evaluation again

  do we still need sizeThres?

Member pcl::gpu::people::LUT_max_part_size []
  read this from XML file
Member pcl::gpu::people::part_t
  implement label 25 to 29
Member pcl::gpu::SeededHueSegmentation::getSearchMethod ()
  fix this for a generic search tree
Member pcl::gpu::SeededHueSegmentation::segment (PointIndices &indices_in, PointIndices &indices_out)
  what do we do if input isn't a PointXYZ cloud?
Member pcl::IndicesAllocator
  Remove with C++20
Member pcl::is_invocable_v
  : Remove in C++17
Member pcl::IterativeClosestPoint< PointSource, PointTarget, Scalar >::IterativeClosestPoint (const IterativeClosestPoint &)=delete
  : remove deleted ctors and assignments operations after resolving the issue
Member pcl::PointXYZRGBAtoXYZHSV (const PointXYZRGBA &in, PointXYZHSV &out)
  include the A parameter but how?
Class pcl::registration::CorrespondenceRejectorFeatures
  explain this better.
Member pcl::remove_cvref_t
  : Remove in C++17
Member pcl::SampleConsensusModel< PointT >::setRadiusLimits (const double &min_radius, const double &max_radius)
  change this to set limits on the entire model
Member pcl::SampleConsensusModelSphere< PointT >::projectPoints (const Indices &inliers, const Eigen::VectorXf &model_coefficients, PointCloud &projected_points, bool copy_data_fields=true) const override
  implement this.
Member pcl::search::OrganizedNeighbor< PointT >::nearestKSearch (const PointT &p_q, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override
  still need to implements this functionality
Member pcl::seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGBL >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)

  look how to make this templated!

Member pcl::seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const search::Search< PointXYZRGB >::Ptr &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)

  look how to make this templated!

Member pcl::SurfaceNormalModality< PointInT >::computeAndQuantizeSurfaceNormals2 ()

  Should also need camera model, or at least focal lengths? Replace distance_threshold with mask?

  Magic number 1150 is focal length? This is something like f in SXGA mode, but in VGA is more like 530.

Member pcl::toPCLPointCloud2 (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
  msg.is_bigendian = ?;
Member pcl::visualization::PointCloudColorHandlerHSVField< PointT >::getColor () const override
  do this with the point_types_conversion in common, first template it!