Descriptor3D is the abstract base class for all descriptors that operate on 3-D data. All inheriting classes define all necessary parameters in their constructor. Hence, after instantiation, all descriptors can compute feature values through the compute() method. The number of feature values the descriptor generates on success is given by getResultSize() More...

#include <descriptor_3d.h>

Inheritance diagram for Descriptor3D:

[legend]

List of all members.

Public Member Functions
virtual void	clearShared ()=0
	Clears the shared information this Descriptor3D is using so the information is computed from scratch on the next compute() call.
void	compute (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const geometry_msgs::Point32 * > &interest_pts, std::vector< std::vector< float > > &results)
	Computes feature values for each specified interest point.
void	compute (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const std::vector< int > * > &interest_region_indices, std::vector< std::vector< float > > &results)
	Computes feature values for each interest region of points.
	Descriptor3D ()
	Abstract constructor.
virtual std::string	getName () const =0
	Returns a string that is unique for the current param settings.
unsigned int	getResultSize () const
	Returns the number of feature values this descriptor computes on success.
virtual	~Descriptor3D ()=0
Static Public Member Functions
Utility methods
static unsigned int	computeAndConcatFeatures (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const geometry_msgs::Point32 * > &interest_pts, std::vector< Descriptor3D * > &descriptors_3d, std::vector< boost::shared_array< const float > > &concatenated_features)
	Utility function to compute multiple descriptor feature around interest points and concatenate the results into a single vector.
static unsigned int	computeAndConcatFeatures (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const std::vector< int > * > &interest_region_indices, std::vector< Descriptor3D * > &descriptors_3d, std::vector< boost::shared_array< const float > > &concatenated_features)
	Utility function to compute multiple descriptor feature around interest regions and concatenate the results into a single vector.
Public Attributes
bool	debug_
	Whether to display the features as they are computed.
Protected Member Functions
virtual void	doComputation (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const geometry_msgs::Point32 * > &interest_pts, std::vector< std::vector< float > > &results)=0
	Does the actual computation after any pre-computations.
virtual void	doComputation (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const std::vector< int > * > &interest_region_indices, std::vector< std::vector< float > > &results)=0
	Does the actual computation after any pre-computations.
virtual int	precompute (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const geometry_msgs::Point32 * > &interest_pts)=0
	Method to do any setup pre-computation necessary for the inheriting descriptor.
virtual int	precompute (const sensor_msgs::PointCloud &data, cloud_kdtree::KdTree &data_kdtree, const std::vector< const std::vector< int > * > &interest_region_indices)=0
	Method to do any setup pre-computation necessary for the inheriting descriptor.
Protected Attributes
unsigned int	result_size_
	The number of feature values the inheriting descriptor computes on success.
bool	result_size_defined_
	Flag if the inheriting descriptor has defined the result size.
Static Private Member Functions
static void	concatenateFeatures (const std::vector< std::vector< std::vector< float > > > &all_descriptor_results, const unsigned int nbr_samples, const unsigned int nbr_concatenated_vals, std::vector< boost::shared_array< const float > > &concatenated_features)
	Concatenates the resulting feature descriptor values.

Detailed Description

Descriptor3D is the abstract base class for all descriptors that operate on 3-D data. All inheriting classes define all necessary parameters in their constructor. Hence, after instantiation, all descriptors can compute feature values through the compute() method. The number of feature values the descriptor generates on success is given by getResultSize()

Definition at line 72 of file descriptor_3d.h.

Constructor & Destructor Documentation

Descriptor3D::Descriptor3D ( )

Abstract constructor.

Definition at line 42 of file descriptor_3d.cpp.

Descriptor3D::~Descriptor3D ( ) [pure virtual]

Definition at line 52 of file descriptor_3d.cpp.

Member Function Documentation

virtual void Descriptor3D::clearShared ( ) [pure virtual]

Clears the shared information this Descriptor3D is using so the information is computed from scratch on the next compute() call.

Implemented in SpinImageCustom, SpinImageNormal, SpinImageTangent, BoundingBoxSpectral, BoundingBoxRaw, OrientationNormal, OrientationTangent, ShapeSpectral, Channel, Position, and Curvature.

void Descriptor3D::compute	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const geometry_msgs::Point32 * > &	interest_pts,
		std::vector< std::vector< float > > &	results
	)

Computes feature values for each specified interest point.

See the inherited class constructor for the type of features computed and necessary parameters

Parameters:

data	Point cloud of the data
data_kdtree	K-D tree representation of data
interest_pts	List of interest points to compute features for
results	Vector to hold computed vector of features for each interest point. If the features could not be computed for an interest point i, then results[i].size() == 0

Definition at line 60 of file descriptor_3d.cpp.

void Descriptor3D::compute	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const std::vector< int > * > &	interest_region_indices,
		std::vector< std::vector< float > > &	results
	)

Computes feature values for each interest region of points.

See the inherited class constructor for the type of features computed and necessary parameters

Parameters:

data	Point cloud of the data
data_kdtree	K-D tree representation of data
interest_region_indices	List of groups of indices into data that represent an interest region
results	Vector to hold computed vector of features for each interest region. If the features could not be computed for an interest region i, then results[i].size() == 0

static unsigned int Descriptor3D::computeAndConcatFeatures	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const geometry_msgs::Point32 * > &	interest_pts,
		std::vector< Descriptor3D * > &	descriptors_3d,
		std::vector< boost::shared_array< const float > > &	concatenated_features
	)		`[static]`

Utility function to compute multiple descriptor feature around interest points and concatenate the results into a single vector.

This method clears out any pre-computed shared information among the descriptors before calculating the new features.

Parameters:

data	See Descriptor3D::compute
data_kdtree	See Descriptor3D::compute
interest_pts	See Descriptor3D::compute
descriptors_3d	List of various feature descriptors to compute on each interest point
concatenated_features	List containing the concatenated features from the descriptors if they were ALL successful for the interest point. If one descriptor failed for interest point i, then concatenated_features[i].get() == NULL

Returns:: The total number of concatenated feature values

static unsigned int Descriptor3D::computeAndConcatFeatures	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const std::vector< int > * > &	interest_region_indices,
		std::vector< Descriptor3D * > &	descriptors_3d,
		std::vector< boost::shared_array< const float > > &	concatenated_features
	)		`[static]`

Utility function to compute multiple descriptor feature around interest regions and concatenate the results into a single vector.

This method clears out any pre-computed shared information among the descriptors before calculating the new features.

Parameters:

data	See Descriptor3D::compute
data_kdtree	See Descriptor3D::compute
interest_region_indices	See Descriptor3D::compute
descriptors_3d	List of various feature descriptors to compute on each interest point
concatenated_features	List containing the concatenated features from the descriptors if they were ALL successful for the interest region. If one descriptor failed for interest region i, then concatenated_features[i].get() == NULL

Returns:: The total number of concatenated feature values

void Descriptor3D::concatenateFeatures	(	const std::vector< std::vector< std::vector< float > > > &	all_descriptor_results,
		const unsigned int	nbr_samples,
		const unsigned int	nbr_concatenated_vals,
		std::vector< boost::shared_array< const float > > &	concatenated_features
	)		`[static, private]`

Concatenates the resulting feature descriptor values.

Parameters:

all_descriptor_results	The results for each descriptor
nbr_samples	The number of interest points/regions
nbr_concatenated_vals	The total length of all concatenated features from each descriptor
concatenated_features	The concatenated features. NULL indicates could not successfully compute descriptor for sample

Definition at line 116 of file descriptor_3d.cpp.

virtual void Descriptor3D::doComputation	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const geometry_msgs::Point32 * > &	interest_pts,
		std::vector< std::vector< float > > &	results
	)		`[protected, pure virtual]`

Does the actual computation after any pre-computations.

See also:: Descriptor3D::compute()

Implemented in Position, ShapeSpectral, Channel, Curvature, NeighborhoodFeature, and OrientationGeneric.

virtual void Descriptor3D::doComputation	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const std::vector< int > * > &	interest_region_indices,
		std::vector< std::vector< float > > &	results
	)		`[protected, pure virtual]`

Does the actual computation after any pre-computations.

See also:: Descriptor3D::compute()

Implemented in Position, ShapeSpectral, Channel, Curvature, NeighborhoodFeature, and OrientationGeneric.

virtual std::string Descriptor3D::getName ( ) const [pure virtual]

Returns a string that is unique for the current param settings.

Returns:: the name of this feature.

Implemented in SpinImageCustom, SpinImageNormal, SpinImageTangent, BoundingBoxSpectral, BoundingBoxRaw, OrientationNormal, OrientationTangent, Position, ShapeSpectral, Channel, and Curvature.

unsigned int Descriptor3D::getResultSize ( ) const [inline]

Returns the number of feature values this descriptor computes on success.

Returns:: the number of feature values this descriptor computes on success

Definition at line 140 of file descriptor_3d.h.

virtual int Descriptor3D::precompute	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const geometry_msgs::Point32 * > &	interest_pts
	)		`[protected, pure virtual]`

Method to do any setup pre-computation necessary for the inheriting descriptor.

Example: estimating normals for each interest point.

Parameters:

data	Point cloud of the data
data_kdtree	K-D tree representation of data
interest_pts	List of interest points for feature computation

Implemented in SpinImageCustom, SpinImageNormal, SpinImageTangent, BoundingBoxSpectral, BoundingBoxRaw, Position, OrientationNormal, OrientationTangent, ShapeSpectral, Channel, and Curvature.

virtual int Descriptor3D::precompute	(	const sensor_msgs::PointCloud &	data,
		cloud_kdtree::KdTree &	data_kdtree,
		const std::vector< const std::vector< int > * > &	interest_region_indices
	)		`[protected, pure virtual]`

Method to do any setup pre-computation necessary for the inheriting descriptor.

Example: estimating normals for each interest point.

Parameters:

data	Point cloud of the data
data_kdtree	K-D tree representation of data
interest_region_indices	List of groups of indices into data that represent an interest region for feature computation

Implemented in SpinImageCustom, SpinImageNormal, SpinImageTangent, BoundingBoxSpectral, BoundingBoxRaw, Position, ShapeSpectral, OrientationNormal, OrientationTangent, Curvature, and Channel.

Member Data Documentation

bool Descriptor3D::debug_

Whether to display the features as they are computed.

Definition at line 211 of file descriptor_3d.h.

unsigned int Descriptor3D::result_size_ [protected]

The number of feature values the inheriting descriptor computes on success.

Definition at line 272 of file descriptor_3d.h.

bool Descriptor3D::result_size_defined_ [protected]

Flag if the inheriting descriptor has defined the result size.

Definition at line 275 of file descriptor_3d.h.

The documentation for this class was generated from the following files:

Public Member Functions

Static Public Member Functions

Public Attributes

Protected Member Functions

Protected Attributes

Static Private Member Functions

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation