Definition of search parameters. More...

#include <cvb/dnc/search_parameters.hpp>

Public Member Functions
	SearchParameters ()=default
	Default search parameters. More...

double	HypothesesThreshold () const noexcept
	Get minimum feature score for hypotheses generation. More...

void	SetHypothesesThreshold (double value)
	Set minimum feature score for hypotheses generation. More...

int	DerivativePatchSize () const noexcept
	Get smoothing area in pixels for gradient and normal calculation. More...

void	SetDerivativePatchSize (int value)
	Set smoothing area in pixels for gradient and normal calculation. More...

double	IndifferentRadius () const noexcept
	Get fraction of template size which accounts for a single object. More...

void	SetIndifferentRadius (double value)
	Set fraction of template size which accounts for a single object. More...

int	PartsToFind () const noexcept
	Get the maximum number of objects to find. More...

void	SetPartsToFind (int value)
	Set the maximum number of objects to find. More...

bool	RawResultsOnly () const noexcept
	Get the raw results flag. More...

void	SetRawResultsOnly (bool value) noexcept
	Set the raw results flag. More...

int	ICPShrink () const noexcept
	Get the subsample factor for ICP. More...

void	SetICPShrink (int value)
	Set the subsample factor for ICP. More...

int	ICPMaxIterations () const noexcept
	Get the maximum number of iterations of the ICP algorithm. More...

void	SetICPMaxIterations (int value)
	Set the maximum number of iterations of the ICP algorithm. More...

double	PrecisionThreshold () const noexcept
	Get precision threshold. More...

void	SetPrecisionThreshold (double value)
	Set precision threshold. More...

double	MinCoverage () const noexcept
	Get minimum coverage. More...

void	SetMinCoverage (double value)
	Set minimum coverage. More...

double	MaxOcclusion () const noexcept
	Get maximum occlusion. More...

void	SetMaxOcclusion (double value)
	Set maximum occlusion. More...

double	MaxInconsistency () const noexcept
	Get maximum inconsistency. More...

void	SetMaxInconsistency (double value)
	Set maximum inconsistency. More...

double	MinScore () const noexcept
	Get minimum score. More...

void	SetMinScore (double value)
	Set minimum score. More...

Detailed Description

Definition of search parameters.

Search parameters strongly influence the search results. Likewise, they have great influence on the timing of a search operation.

Examples: DNC/CppDncConsole.

Constructor & Destructor Documentation

◆ SearchParameters()

SearchParameters ( )

default

Default search parameters.

Exceptions

Does	not throw any exception.

Member Function Documentation

◆ DerivativePatchSize()

int DerivativePatchSize ( ) const

inlinenoexcept

Get smoothing area in pixels for gradient and normal calculation.

A detailed description of this parameter can be found at the corresponding setting function SetDerivativePatchSize.

Returns: The patch size.

Exceptions

Does	not throw any exception.

◆ HypothesesThreshold()

double HypothesesThreshold ( ) const

inlinenoexcept

Get minimum feature score for hypotheses generation.

A detailed description of this parameter can be found at the corresponding setting function SetHypothesesThreshold.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ ICPMaxIterations()

int ICPMaxIterations ( ) const

inlinenoexcept

Get the maximum number of iterations of the ICP algorithm.

A detailed description of this parameter can be found at the corresponding setting function SetICPMaxIterations.

Returns: The number of iterations.

Exceptions

Does	not throw any exception.

◆ ICPShrink()

int ICPShrink ( ) const

inlinenoexcept

Get the subsample factor for ICP.

A detailed description of this parameter can be found at the corresponding setting function SetICPShrink.

Returns: The subsample factor.

Exceptions

Does	not throw any exception.

◆ IndifferentRadius()

double IndifferentRadius ( ) const

inlinenoexcept

Get fraction of template size which accounts for a single object.

A detailed description of this parameter can be found at the corresponding setting function SetIndifferentRadius.

Returns: The indifferent radius.

Exceptions

Does	not throw any exception.

◆ MaxInconsistency()

double MaxInconsistency ( ) const

inlinenoexcept

Get maximum inconsistency.

A detailed description of this parameter can be found at the corresponding setting function SetMaxInconsistency.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ MaxOcclusion()

double MaxOcclusion ( ) const

inlinenoexcept

Get maximum occlusion.

A detailed description of this parameter can be found at the corresponding setting function SetMaxOcclusion.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ MinCoverage()

double MinCoverage ( ) const

inlinenoexcept

Get minimum coverage.

A detailed description of this parameter can be found at the corresponding setting function SetMinCoverage.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ MinScore()

double MinScore ( ) const

inlinenoexcept

Get minimum score.

A detailed description of this parameter can be found at the corresponding setting function SetMinScore.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ PartsToFind()

int PartsToFind ( ) const

inlinenoexcept

Get the maximum number of objects to find.

A detailed description of this parameter can be found at the corresponding setting function SetPartsToFind.

Returns: The number of parts to find.

Exceptions

Does	not throw any exception.

◆ PrecisionThreshold()

double PrecisionThreshold ( ) const

inlinenoexcept

Get precision threshold.

A detailed description of this parameter can be found at the corresponding setting function SetPrecisionThreshold.

Returns: The threshold.

Exceptions

Does	not throw any exception.

◆ RawResultsOnly()

bool RawResultsOnly ( ) const

inlinenoexcept

Get the raw results flag.

A detailed description of this parameter can be found at the corresponding setting function SetRawResultsOnly.

Returns: True if set on, false otherwise.

Exceptions

Does	not throw any exception.

◆ SetDerivativePatchSize()

void SetDerivativePatchSize ( int value )

inline

Set smoothing area in pixels for gradient and normal calculation.

This value controls which local environment in the depth image is used to calculate gradients and normals. Minimum is 3. Larger values result in a smoothing of the depth image. This value should be odd. Typical values are in the range 3..9.

Parameters

[in] value The patch size.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetHypothesesThreshold()

void SetHypothesesThreshold ( double value )

inline

Set minimum feature score for hypotheses generation.

This value controls which areas of the depth image are used as candidates for closer examination. The feature score is calculated from the correspondences of gradients and normals between all models and the actual point cloud data. The threshold should be chosen so that on the one hand all object candidates are found, on the other hand as few false candidates as possible are generated. Typical values are in the range between 0.9 ... 1.0. Disturbances in the point cloud, missing or spurious data may make it necessary to reduce the value. The minimum value is 0.5.

To find a usable threshold it is recommended to set the flag SetRawResultsOnly().

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetICPMaxIterations()

void SetICPMaxIterations ( int value )

inline

Set the maximum number of iterations of the ICP algorithm.

This value specifies the maximum number of iterations of the ICP algorithm. Increasing the value may increase the accuracy of the result, while possibly increasing the processing time. A typical value is 10.

Parameters

[in] value The number of iterations.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetICPShrink()

void SetICPShrink ( int value )

inline

Set the subsample factor for ICP.

This value specifies the factor by which the area of a found candidate is reduced before the exact position of the object is determined by means of an ICP algorithm. The minimum allowed value of 1 means no reduction (highest accuracy). With increasing reduction, the processing speed increases, but at the same time the accuracy of the results also decrease. Typical values are in a range 1..4.

Parameters

[in] value The subsample factor.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetIndifferentRadius()

void SetIndifferentRadius ( double value )

inline

Set fraction of template size which accounts for a single object.

This value specifies within which vicinity of a found candidate no further candidates are searched for. The value 1 indicates the largest extent of the learned object. For elongated objects that are close to each other, a smaller value may have to be selected. The minimum value is 0.5.

Parameters

[in] value The indifferent radius.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetMaxInconsistency()

void SetMaxInconsistency ( double value )

inline

Set maximum inconsistency.

This value is a threshold (0..1) that specifies the maximum allowed part of the model view to be insconsistent with the point cloud data in order for the hit to be counted. Inconsistency is defined to be point cloud data which is beyond the model. A typical value may be 0.2. It is influenced by PrecisionThreshold.

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetMaxOcclusion()

void SetMaxOcclusion ( double value )

inline

Set maximum occlusion.

This value is a threshold (0..1) that specifies the maximum allowed part of the model view which is occluded by the point cloud data in order for the hit to be counted. Occlusion is defined to be point cloud data lying between the model and the sensor. A typical value may be 0.2. It is influenced by PrecisionThreshold.

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetMinCoverage()

void SetMinCoverage ( double value )

inline

Set minimum coverage.

This value is a threshold (0..1) that specifies the minimum required coverage of the model view by the point cloud data in order for the hit to be counted. A typical value may be 0.8. It is influenced by PrecisionThreshold.

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetMinScore()

void SetMinScore ( double value )

inline

Set minimum score.

This value is a threshold (0..1) that determines whether the candidate is counted as a hit. For this, a hash similarity score between final model view and point cloud data must exceed this limit. A typical value may be 0.8.

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetPartsToFind()

void SetPartsToFind ( int value )

inline

Set the maximum number of objects to find.

This value specifies the maximum number of objects to be detected. A value of zero means that all objects should be found.

Parameters

[in] value The number of parts to find.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetPrecisionThreshold()

void SetPrecisionThreshold ( double value )

inline

Set precision threshold.

The calculation of the result score is based on deviations between the CAD model and the point cloud data. This value determines which deviation is considered tolerable, inconsistent or occlusion. This value depends on the quality of the point cloud data. A typical value is 2 mm, the minimum allowed value is 0.

Parameters

[in] value The threshold.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

◆ SetRawResultsOnly()

void SetRawResultsOnly ( bool value )

inlinenoexcept

Set the raw results flag.

If this flag is set, candidate locations are considered as hits without further investigation of these candidates. In this case, only parameters HypothesesThreshold, PartsToFind and MinScore are decisive for finding objects. If found candidates are indeed true object hits, the result values for SearchResult.Position, SearchResult.RotationVector and SearchResult.Theta are only rough in a sense, that no fine tuning (ICP) takes place.

Also, in this case the reported SearchResult.Score values coincide with the feature scores, which makes it possible to determine a useful value for HypothesesThreshold.

Parameters

[in] value True to set on, false otherwise.

Exceptions

Does	not throw any exception.

Examples: DNC/CppDncConsole.

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ SearchParameters()

Member Function Documentation

◆ DerivativePatchSize()

◆ HypothesesThreshold()

◆ ICPMaxIterations()

◆ ICPShrink()

◆ IndifferentRadius()

◆ MaxInconsistency()

◆ MaxOcclusion()

◆ MinCoverage()

◆ MinScore()

◆ PartsToFind()

◆ PrecisionThreshold()

◆ RawResultsOnly()

◆ SetDerivativePatchSize()

◆ SetHypothesesThreshold()

◆ SetICPMaxIterations()

◆ SetICPShrink()

◆ SetIndifferentRadius()

◆ SetMaxInconsistency()

◆ SetMaxOcclusion()

◆ SetMinCoverage()

◆ SetMinScore()

◆ SetPartsToFind()

◆ SetPrecisionThreshold()

◆ SetRawResultsOnly()