opentl::modalities::DataFusion Class Reference

Static data fusion class. It inherits from the modalities:Modality interface, so it can be flexibly combined with the features. ASSUMPTIONS:

• the children output levels of one DataFusion class instance must be of the same level E.g. if you want to fuse the output of two pixel level children and one feature level child you have to cascade two DataFusion classes. DF1 instance fuses pixel level to feature level and DF2 instance fuses the output of DF1 with the feature level child.

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Inherits opentl::modalities::Modality.

List of all members.

Public Types
Public Member Functions
virtual modalities::Modality *	clone () const
	Deep cloning.
	DataFusion (const DataFusion &c)
	Copy Constructor.
	DataFusion (opentl::modelprojection::Warp *warp, int camIdx, opentl::modelprojection::GLRenderer *GLRender=NULL)
	Copy Constructor.
const opentl::core::cvdata::Image &	getFusionImage ()
virtual void	init ()
	Initialize class (clean parameter status).
virtual int	matchFeatLevel (const TargetPtrVector &targets, T_MEAS_FEATPtrVector &outputMeas, std::size_t partitionIdx)
	Matching on feature level match projected model features with detected image features.
virtual int	matchObjLevel (const TargetPtrVector &targets, T_MEAS_OBJPtrVector &outputMeas, std::size_t partitionIdx)
	Matching on object level compute a local, maximum-likelihood estimate of pose (evtl. state), using either pixel- or feature-level likelihood functions.
virtual int	matchPixLevel (const TargetPtrVector &targets, T_MEAS_PIXPtrVector &outputMeas, std::size_t partitionIdx)
	Here "MATCH" = "FUSION"!
virtual int	sampleModelFeatures (const TargetPtrVector &targets)
	Sample model features for all children.
virtual int	updateModelFeatures (const TargetPtrVector &targets)
	Update online features for all children.
virtual	~DataFusion ()
	Destructor.
Protected Attributes
int	mCurrentPartitionIdx
	Current partition index for multi-threading.
TargetPtrVector	mTmpTarget
	Temporary state NOTE: this is needed by the static function "staticSimilarityEval" (for the simplex optimizer).

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Detailed Description

Static data fusion class. It inherits from the modalities:Modality interface, so it can be flexibly combined with the features. ASSUMPTIONS:

• the children output levels of one DataFusion class instance must be of the same level E.g. if you want to fuse the output of two pixel level children and one feature level child you have to cascade two DataFusion classes. DF1 instance fuses pixel level to feature level and DF2 instance fuses the output of DF1 with the feature level child.

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Member Enumeration Documentation

enum opentl::modalities::DataFusion::OfflineParameters

Enumerator:

OFFLINE_COUNT

Reimplemented from opentl::modalities::Modality.

enum opentl::modalities::DataFusion::OnlineParameters

Enumerator:

fusionAlgo	Data fusion modality (scheme for static fusion, input/output levels for z).
fusionAlgoPixelLevel_Weights	Weight vector<double> for pixel-level, weighted average fusion.
fusionAlgoPixelLevel_matchPixUsingResidualImage	(bool) Compute residual image or just scalar residual
fusionAlgoPixelLevel_matchPixelRInvVariance	(double) Inverse variance of the pixel-level residual
fusionAlgoObjectUpgrade_Epsilon	Exit condition: minimum error for one delta step.
fusionAlgoObjectUpgrade_CovRVector	vector containing the covariance output values TODO: use math::Vector
fusionAlgoObjectUpgrade_UseFullCovarianceMatrix	Flag whether to use the full Covariance Matrix as output or only the diagonal (default).
fusionAlgoObjectUpgrade_EnableMultiThreadingPerChildFeature	create a thread per feature matchxxxLevel() function call
fusionAlgoObjectUpgrade_usePrior	Whether to use the prediction (prior) Gaussian to regularize Gauss-Newton optimization.
fusionAlgoObjectUpgrade_GaussNewton_enableDampingFactor	flag to enable damping factor in case of a singular matrix
fusionAlgoObjectUpgrade_GaussNewton_dampingFactorDeterminantMinThreshold	Whether to use the invert covariance in the Gauss-Newton algorithm NOTE: it makes sense only if the measurements have a variable covariance.
fusionAlgoObjectUpgrade_GaussNewton_dampingFactorMax	maximum damping factor
fusionAlgoObjectUpgrade_GaussNewton_MEstimator	M Estimator to use.
fusionAlgoObjectUpgrade_GaussNewton_MEstimatorThresh	M Estimator threshold.
ONLINE_COUNT

Reimplemented from opentl::modalities::Modality.

enum opentl::modalities::DataFusion::T_FUSION_ALGO

Possible static fusion schemes.

Enumerator:

PIXEL_WA
PIXEL_PRODUCT
PIXEL_VOTING
PIXEL_FUZZY
OBJECT_UPGRADE_GAUSS_NEWTON

enum opentl::modalities::DataFusion::VotingMode

Possible voting schemes for pixel-level.

Enumerator:

UNANIMITY
BYZANTINE
MAJORITY
MOUTN

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Constructor & Destructor Documentation

opentl::modalities::DataFusion::DataFusion	(	opentl::modelprojection::Warp *	warp,
		int	camIdx,
		opentl::modelprojection::GLRenderer *	GLRender = NULL
	)

Copy Constructor.

opentl::modalities::DataFusion::DataFusion

(

const DataFusion &

c

)

Copy Constructor.

virtual opentl::modalities::DataFusion::~DataFusion

(

)

[virtual]

Destructor.

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Member Function Documentation

virtual modalities::Modality* opentl::modalities::DataFusion::clone

(

)

const [virtual]

Deep cloning.

Implements opentl::modalities::Modality.

const opentl::core::cvdata::Image& opentl::modalities::DataFusion::getFusionImage

(

)

virtual void opentl::modalities::DataFusion::init

(

)

[virtual]

Initialize class (clean parameter status).

Reimplemented from opentl::modalities::Modality.

virtual int opentl::modalities::DataFusion::matchFeatLevel	(	const TargetPtrVector &	targets,
		T_MEAS_FEATPtrVector &	outputMeas,
		std::size_t	partitionIdx
	)			[virtual]

Matching on feature level

• match projected model features with detected image features.

Parameters:

	states	Predicted state
	outputMeas	Feature-space measurements and residuals

Reimplemented from opentl::modalities::Modality.

virtual int opentl::modalities::DataFusion::matchObjLevel	(	const TargetPtrVector &	targets,
		T_MEAS_OBJPtrVector &	outputMeas,
		std::size_t	partitionIdx
	)			[virtual]

Matching on object level

• compute a local, maximum-likelihood estimate of pose (evtl. state), using either pixel- or feature-level likelihood functions.

Parameters:

	states	Predicted state
	outputMeas	State-space measurement and residuals (expected state = prediction, observed state = ML estimate)

Reimplemented from opentl::modalities::Modality.

virtual int opentl::modalities::DataFusion::matchPixLevel	(	const TargetPtrVector &	targets,
		T_MEAS_PIXPtrVector &	outputMeas,
		std::size_t	partitionIdx
	)			[virtual]

Here "MATCH" = "FUSION"!

Reimplemented from opentl::modalities::Modality.

virtual int opentl::modalities::DataFusion::sampleModelFeatures

(

const TargetPtrVector &

targets

)

[virtual]

Sample model features for all children.

Reimplemented from opentl::modalities::Modality.

virtual int opentl::modalities::DataFusion::updateModelFeatures

(

const TargetPtrVector &

targets

)

[virtual]

Update online features for all children.

Reimplemented from opentl::modalities::Modality.

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Member Data Documentation

int opentl::modalities::DataFusion::mCurrentPartitionIdx [protected]

Current partition index for multi-threading.

TargetPtrVector opentl::modalities::DataFusion::mTmpTarget [protected]

Temporary state NOTE: this is needed by the static function "staticSimilarityEval" (for the simplex optimizer).