cv::detail Namespace Reference

Namespaces
namespace	contrib_feature
namespace	kalman_filters
namespace	online_boosting
namespace	tbm
namespace	tld
namespace	tracking

Classes
class	AffineBasedEstimator
	Affine transformation based estimator. More...
class	AffineBestOf2NearestMatcher
	Features matcher similar to cv::detail::BestOf2NearestMatcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf. More...
class	AffineWarper
	Affine warper that uses rotations and translations. More...
class	AugmentedUnscentedKalmanFilterParams
	Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Unscented Kalman filter. More...
class	BaseClassifier
class	BestOf2NearestMatcher
	Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf. More...
class	BestOf2NearestRangeMatcher
class	Blender
	Base class for all blenders. More...
class	BlocksChannelsCompensator
	Exposure compensator which tries to remove exposure related artifacts by adjusting image block on each channel. More...
class	BlocksCompensator
	Exposure compensator which tries to remove exposure related artifacts by adjusting image blocks. More...
class	BlocksGainCompensator
	Exposure compensator which tries to remove exposure related artifacts by adjusting image block intensities, see [280] for details. More...
class	BundleAdjusterAffine
	Bundle adjuster that expects affine transformation represented in homogeneous coordinates in R for each camera param. Implements camera parameters refinement algorithm which minimizes sum of the reprojection error squares. More...
class	BundleAdjusterAffinePartial
	Bundle adjuster that expects affine transformation with 4 DOF represented in homogeneous coordinates in R for each camera param. Implements camera parameters refinement algorithm which minimizes sum of the reprojection error squares. More...
class	BundleAdjusterBase
	Base class for all camera parameters refinement methods. More...
class	BundleAdjusterRay
	Implementation of the camera parameters refinement algorithm which minimizes sum of the distances between the rays passing through the camera center and a feature. : More...
class	BundleAdjusterReproj
	Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection error squares. More...
struct	CameraParams
	Describes camera parameters. More...
class	ChannelsCompensator
	Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities on each channel independently. More...
class	ClassifierThreshold
struct	CompressedRectilinearPortraitProjector
class	CompressedRectilinearPortraitWarper
struct	CompressedRectilinearProjector
class	CompressedRectilinearWarper
class	CvFeatureEvaluator
class	CvFeatureParams
class	CvHaarEvaluator
class	CvHaarFeatureParams
class	CvHOGEvaluator
struct	CvHOGFeatureParams
class	CvLBPEvaluator
struct	CvLBPFeatureParams
class	CvParams
struct	CylindricalPortraitProjector
class	CylindricalPortraitWarper
struct	CylindricalProjector
class	CylindricalWarper
	Warper that maps an image onto the x*x + z*z = 1 cylinder. More...
class	CylindricalWarperGpu
class	Detector
class	DisjointSets
class	DpSeamFinder
class	EstimatedGaussDistribution
class	Estimator
	Rotation estimator base class. More...
class	ExposureCompensator
	Base class for all exposure compensators. More...
class	FeatherBlender
	Simple blender which mixes images at its borders. More...
class	FeaturesMatcher
	Feature matchers base class. More...
struct	FisheyeProjector
class	FisheyeWarper
class	GainCompensator
	Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities, see [41] and [306] for details. More...
class	Graph
class	GraphCutSeamFinder
	Minimum graph cut-based seam estimator. See details in [153] . More...
class	GraphCutSeamFinderBase
	Base class for all minimum graph-cut-based seam estimators. More...
struct	GraphEdge
class	HomographyBasedEstimator
	Homography based rotation estimator. More...
struct	ImageFeatures
	Structure containing image keypoints and descriptors. More...
class	LevMarqBackend
class	LevMarqBase
	Base class for Levenberg-Marquadt solvers. More...
struct	MatchesInfo
	Structure containing information about matches between two images. More...
struct	MercatorProjector
class	MercatorWarper
class	MultiBandBlender
	Blender which uses multi-band blending algorithm (see [45]). More...
class	NoBundleAdjuster
	Stub bundle adjuster that does nothing. More...
class	NoExposureCompensator
	Stub exposure compensator which does nothing. More...
class	NoSeamFinder
	Stub seam estimator which does nothing. More...
class	PairwiseSeamFinder
	Base class for all pairwise seam estimators. More...
struct	PaniniPortraitProjector
class	PaniniPortraitWarper
struct	PaniniProjector
class	PaniniWarper
struct	PlanePortraitProjector
class	PlanePortraitWarper
struct	PlaneProjector
class	PlaneWarper
	Warper that maps an image onto the z = 1 plane. More...
class	PlaneWarperGpu
class	PoseGraph
struct	ProjectorBase
	Base class for warping logic implementation. More...
class	RotationWarper
	Rotation-only model image warper interface. More...
class	RotationWarperBase
	Base class for rotation-based warper using a detail::ProjectorBase_ derived class. More...
class	SeamFinder
	Base class for a seam estimator. More...
struct	SphericalPortraitProjector
class	SphericalPortraitWarper
struct	SphericalProjector
class	SphericalWarper
	Warper that maps an image onto the unit sphere located at the origin. More...
class	SphericalWarperGpu
struct	StereographicProjector
class	StereographicWarper
class	StrongClassifierDirectSelection
class	Submap
class	SubmapManager
	: Manages all the created submaps for a particular scene More...
class	Timelapser
class	TimelapserCrop
class	TrackerContribFeature
	Abstract base class for TrackerContribFeature that represents the feature. More...
class	TrackerContribFeatureHAAR
	TrackerContribFeature based on HAAR features, used by TrackerMIL and many others algorithms. More...
class	TrackerContribFeatureSet
	Class that manages the extraction and selection of features. More...
class	TrackerContribSampler
	Class that manages the sampler in order to select regions for the update the model of the tracker [AAM] Sampling e Labeling. See table I and section III B. More...
class	TrackerContribSamplerAlgorithm
	Abstract base class for TrackerContribSamplerAlgorithm that represents the algorithm for the specific sampler. More...
class	TrackerContribSamplerCSC
	TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL. More...
class	TrackerFeature
	Abstract base class for TrackerFeature that represents the feature. More...
class	TrackerFeatureFeature2d
	TrackerContribFeature based on Feature2D. More...
class	TrackerFeatureHOG
	TrackerContribFeature based on HOG. More...
class	TrackerFeatureLBP
	TrackerContribFeature based on LBP. More...
class	TrackerFeatureSet
	Class that manages the extraction and selection of features. More...
class	TrackerModel
	Abstract class that represents the model of the target. More...
class	TrackerSampler
	Class that manages the sampler in order to select regions for the update the model of the tracker [AAM] Sampling e Labeling. See table I and section III B. More...
class	TrackerSamplerAlgorithm
	Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific sampler. More...
class	TrackerSamplerCS
	TrackerContribSampler based on CS (current state), used by algorithm TrackerBoosting. More...
class	TrackerSamplerCSC
	TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL. More...
class	TrackerSamplerPF
	This sampler is based on particle filtering. More...
class	TrackerStateEstimator
	Abstract base class for TrackerStateEstimator that estimates the most likely target state. More...
class	TrackerStateEstimatorAdaBoosting
	TrackerStateEstimatorAdaBoosting based on ADA-Boosting. More...
class	TrackerStateEstimatorSVM
	TrackerStateEstimator based on SVM. More...
class	TrackerTargetState
	Abstract base class for TrackerTargetState that represents a possible state of the target. More...
struct	TransverseMercatorProjector
class	TransverseMercatorWarper
class	UkfSystemModel
	Model of dynamical system for Unscented Kalman filter. The interface for dynamical system model. It contains functions for computing the next state and the measurement. It must be inherited for using UKF. More...
class	UnscentedKalmanFilter
	The interface for Unscented Kalman filter and Augmented Unscented Kalman filter. More...
class	UnscentedKalmanFilterParams
	Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter. More...
class	VoronoiSeamFinder
	Voronoi diagram-based seam estimator. More...
class	WeakClassifierHaarFeature

Typedefs
typedef std::vector< std::pair< Ptr< TrackerTargetState >, float > >	ConfidenceMap
	Represents the model of the target at frame \(k\) (all states and scores)
typedef std::vector< Ptr< TrackerTargetState > >	Trajectory
	Represents the estimate states for all frames.

Enumerations
enum	WaveCorrectKind {   WAVE_CORRECT_HORIZ ,   WAVE_CORRECT_VERT ,   WAVE_CORRECT_AUTO }

Functions
template<class Feature >
void	_writeFeatures (const std::vector< Feature > features, FileStorage &fs, const Mat &featureMap)
WaveCorrectKind	autoDetectWaveCorrectKind (const std::vector< Mat > &rmats)
	Tries to detect the wave correction kind depending on whether a panorama spans horizontally or vertically.
float	calcNormFactor (const Mat &sum, const Mat &sqSum)
bool	calibrateRotatingCamera (const std::vector< Mat > &Hs, Mat &K)
void	computeImageFeatures (const Ptr< Feature2D > &featuresFinder, InputArray image, ImageFeatures &features, InputArray mask=noArray())
void	computeImageFeatures (const Ptr< Feature2D > &featuresFinder, InputArrayOfArrays images, std::vector< ImageFeatures > &features, InputArrayOfArrays masks=noArray())
void	computeInteractionMatrix (const cv::Mat &uv, const cv::Mat &depths, const cv::Mat &K, cv::Mat &J)
	Compute the interaction matrix ( [132] [52] [53] ) for a set of 2D pixels. This is usually used in visual servoing applications to command a robot to move at desired pixel locations/velocities. By inverting this matrix, one can estimate camera spatial velocity i.e., the twist.
cv::Vec6d	computeTwist (const cv::Mat &uv, const cv::Mat &duv, const cv::Mat &depths, const cv::Mat &K)
	Compute the camera twist from a set of 2D pixel locations, their velocities, depth values and intrinsic parameters of the camera. The pixel velocities are usually obtained from optical flow algorithms, both dense and sparse flow can be used to compute the flow between images and duv computed by dividing the flow by the time interval between the images.
Ptr< UnscentedKalmanFilter >	createAugmentedUnscentedKalmanFilter (const AugmentedUnscentedKalmanFilterParams &params)
	Augmented Unscented Kalman Filter factory method.
void	createLaplacePyr (InputArray img, int num_levels, std::vector< UMat > &pyr)
void	createLaplacePyrGpu (InputArray img, int num_levels, std::vector< UMat > &pyr)
Ptr< UnscentedKalmanFilter >	createUnscentedKalmanFilter (const UnscentedKalmanFilterParams &params)
	Unscented Kalman Filter factory method.
void	createWeightMap (InputArray mask, float sharpness, InputOutputArray weight)
void	estimateFocal (const std::vector< ImageFeatures > &features, const std::vector< MatchesInfo > &pairwise_matches, std::vector< double > &focals)
	Estimates focal lengths for each given camera.
void	findMaxSpanningTree (int num_images, const std::vector< MatchesInfo > &pairwise_matches, Graph &span_tree, std::vector< int > &centers)
void	focalsFromHomography (const Mat &H, double &f0, double &f1, bool &f0_ok, bool &f1_ok)
	Tries to estimate focal lengths from the given homography under the assumption that the camera undergoes rotations around its centre only.
std::vector< int >	leaveBiggestComponent (std::vector< ImageFeatures > &features, std::vector< MatchesInfo > &pairwise_matches, float conf_threshold)
String	matchesGraphAsString (std::vector< String > &paths, std::vector< MatchesInfo > &pairwise_matches, float conf_threshold)
void	normalizeUsingWeightMap (InputArray weight, InputOutputArray src)
bool	overlapRoi (Point tl1, Point tl2, Size sz1, Size sz2, Rect &roi)
void	renderPointsNormals (InputArray _points, InputArray _normals, OutputArray image, cv::Vec3f lightLoc)
void	renderPointsNormalsColors (InputArray _points, InputArray _normals, InputArray _colors, OutputArray image)
void	restoreImageFromLaplacePyr (std::vector< UMat > &pyr)
void	restoreImageFromLaplacePyrGpu (std::vector< UMat > &pyr)
Rect	resultRoi (const std::vector< Point > &corners, const std::vector< Size > &sizes)
Rect	resultRoi (const std::vector< Point > &corners, const std::vector< UMat > &images)
Rect	resultRoiIntersection (const std::vector< Point > &corners, const std::vector< Size > &sizes)
Point	resultTl (const std::vector< Point > &corners)
void	selectRandomSubset (int count, int size, std::vector< int > &subset)
int &	stitchingLogLevel ()
void	waveCorrect (std::vector< Mat > &rmats, WaveCorrectKind kind)
	Tries to make panorama more horizontal (or vertical).

Function Documentation

renderPointsNormals()

void cv::detail::renderPointsNormals	(	InputArray	_points,
		InputArray	_normals,
		OutputArray	image,
		cv::Vec3f	lightLoc
	)

renderPointsNormalsColors()

void cv::detail::renderPointsNormalsColors	(	InputArray	_points,
		InputArray	_normals,
		InputArray	_colors,
		OutputArray	image
	)