Modifier and Type | Class and Description |
---|---|
class |
BackgroundSubtractorCNT
Background subtraction based on counting.
|
class |
BackgroundSubtractorGMG
Background Subtractor module based on the algorithm given in CITE: Gold2012 .
|
class |
BackgroundSubtractorGSOC
Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.
|
class |
BackgroundSubtractorLSBP
Background Subtraction using Local SVD Binary Pattern.
|
class |
BackgroundSubtractorMOG
Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
|
class |
SyntheticSequenceGenerator
Synthetic frame sequence generator for testing background subtraction algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
Retina
class which allows the Gipsa/Listic Labs model to be used with OpenCV.
|
class |
RetinaFastToneMapping
a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
|
class |
TransientAreasSegmentationModule
class which provides a transient/moving areas segmentation module
perform a locally adapted segmentation by using the retina magno input data Based on Alexandre
BENOIT thesis: "Le système visuel humain au secours de la vision par ordinateur"
3 spatio temporal filters are used:
a first one which filters the noise and local variations of the input motion energy
a second (more powerfull low pass spatial filter) which gives the neighborhood motion energy the
segmentation consists in the comparison of these both outputs, if the local motion energy is higher
to the neighborhood otion energy, then the area is considered as moving and is segmented
a stronger third low pass filter helps decision by providing a smooth information about the
"motion context" in a wider area
|
Modifier and Type | Class and Description |
---|---|
class |
StereoBM
Class for computing stereo correspondence using the block matching algorithm, introduced and
contributed to OpenCV by K.
|
class |
StereoMatcher
The base class for stereo correspondence algorithms.
|
class |
StereoSGBM
The class implements the modified H.
|
Modifier and Type | Method and Description |
---|---|
static Algorithm |
Algorithm.__fromPtr__(long addr) |
Modifier and Type | Class and Description |
---|---|
class |
Layer
This interface class allows to build new Layers - are building blocks of networks.
|
Modifier and Type | Class and Description |
---|---|
class |
BasicFaceRecognizer |
class |
BIF
Implementation of bio-inspired features (BIF) from the paper:
Guo, Guodong, et al.
|
class |
EigenFaceRecognizer |
class |
Facemark
Abstract base class for all facemark models
To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark
### Description
Facemark is a base class which provides universal access to any specific facemark algorithm.
|
class |
FacemarkAAM |
class |
FacemarkKazemi |
class |
FacemarkLBF |
class |
FacemarkTrain
Abstract base class for trainable facemark models
To utilize this API in your program, please take a look at the REF: tutorial_table_of_content_facemark
### Description
The AAM and LBF facemark models in OpenCV are derived from the abstract base class FacemarkTrain, which
provides a unified access to those facemark algorithms in OpenCV.
|
class |
FaceRecognizer
Abstract base class for all face recognition models
All face recognition models in OpenCV are derived from the abstract base class FaceRecognizer, which
provides a unified access to all face recongition algorithms in OpenCV.
|
class |
FisherFaceRecognizer |
class |
LBPHFaceRecognizer |
class |
MACE
Minimum Average Correlation Energy Filter
useful for authentication with (cancellable) biometrical features.
|
Modifier and Type | Class and Description |
---|---|
class |
AgastFeatureDetector
Wrapping class for feature detection using the AGAST method.
|
class |
AKAZE
Class implementing the AKAZE keypoint detector and descriptor extractor, described in CITE: ANB13.
|
class |
BFMatcher
Brute-force descriptor matcher.
|
class |
BRISK
Class implementing the BRISK keypoint detector and descriptor extractor, described in CITE: LCS11 .
|
class |
DescriptorMatcher
Abstract base class for matching keypoint descriptors.
|
class |
FastFeatureDetector
Wrapping class for feature detection using the FAST method.
|
class |
Feature2D
Abstract base class for 2D image feature detectors and descriptor extractors
|
class |
FlannBasedMatcher
Flann-based descriptor matcher.
|
class |
GFTTDetector
Wrapping class for feature detection using the goodFeaturesToTrack function.
|
class |
KAZE
Class implementing the KAZE keypoint detector and descriptor extractor, described in CITE: ABD12 .
|
class |
MSER
Maximally stable extremal region extractor
The class encapsulates all the parameters of the %MSER extraction algorithm (see [wiki
article](http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions)).
|
class |
ORB
Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor
described in CITE: RRKB11 .
|
class |
SimpleBlobDetector
Class for extracting blobs from an image.
|
Modifier and Type | Class and Description |
---|---|
class |
AverageHash
Computes average hash value of the input image
This is a fast image hashing algorithm, but only work on simple case.
|
class |
BlockMeanHash
Image hash based on block mean.
|
class |
ColorMomentHash
Image hash based on color moments.
|
class |
ImgHashBase
The base class for image hash algorithms
|
class |
MarrHildrethHash
Marr-Hildreth Operator Based Hash, slowest but more discriminative.
|
class |
PHash
pHash
Slower than average_hash, but tolerant of minor modifications
This algorithm can combat more variation than averageHash, for more details please refer to CITE: lookslikeit
|
class |
RadialVarianceHash
Image hash based on Radon transform.
|
Modifier and Type | Class and Description |
---|---|
class |
CLAHE
Base class for Contrast Limited Adaptive Histogram Equalization.
|
class |
GeneralizedHough
finds arbitrary template in the grayscale image using Generalized Hough Transform
|
class |
GeneralizedHoughBallard
finds arbitrary template in the grayscale image using Generalized Hough Transform
Detects position only without translation and rotation CITE: Ballard1981 .
|
class |
GeneralizedHoughGuil
finds arbitrary template in the grayscale image using Generalized Hough Transform
Detects position, translation and rotation CITE: Guil1999 .
|
class |
LineSegmentDetector
Line segment detector class
following the algorithm described at CITE: Rafael12 .
|
Modifier and Type | Class and Description |
---|---|
class |
ANN_MLP
Artificial Neural Networks - Multi-Layer Perceptrons.
|
class |
Boost
Boosted tree classifier derived from DTrees
SEE: REF: ml_intro_boost
|
class |
DTrees
The class represents a single decision tree or a collection of decision trees.
|
class |
EM
The class implements the Expectation Maximization algorithm.
|
class |
KNearest
The class implements K-Nearest Neighbors model
SEE: REF: ml_intro_knn
|
class |
LogisticRegression
Implements Logistic Regression classifier.
|
class |
NormalBayesClassifier
Bayes classifier for normally distributed data.
|
class |
RTrees
The class implements the random forest predictor.
|
class |
StatModel
Base class for statistical models in OpenCV ML.
|
class |
SVM
Support Vector Machines.
|
class |
SVMSGD
*************************************************************************************\
Stochastic Gradient Descent SVM Classifier *
\***************************************************************************************
|
Modifier and Type | Class and Description |
---|---|
class |
BaseCascadeClassifier |
Modifier and Type | Class and Description |
---|---|
class |
HistogramPhaseUnwrapping
Class implementing two-dimensional phase unwrapping based on CITE: histogramUnwrapping
This algorithm belongs to the quality-guided phase unwrapping methods.
|
class |
PhaseUnwrapping
Abstract base class for phase unwrapping.
|
Modifier and Type | Class and Description |
---|---|
class |
AlignExposures
The base class for algorithms that align images of the same scene with different exposures
|
class |
AlignMTB
This algorithm converts images to median threshold bitmaps (1 for pixels brighter than median
luminance and 0 otherwise) and than aligns the resulting bitmaps using bit operations.
|
class |
CalibrateCRF
The base class for camera response calibration algorithms.
|
class |
CalibrateDebevec
Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
class |
CalibrateRobertson
Inverse camera response function is extracted for each brightness value by minimizing an objective
function as linear system.
|
class |
MergeDebevec
The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
class |
MergeExposures
The base class algorithms that can merge exposure sequence to a single image.
|
class |
MergeMertens
Pixels are weighted using contrast, saturation and well-exposedness measures, than images are
combined using laplacian pyramids.
|
class |
MergeRobertson
The resulting HDR image is calculated as weighted average of the exposures considering exposure
values and camera response.
|
class |
Tonemap
Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range.
|
class |
TonemapDrago
Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in
logarithmic domain.
|
class |
TonemapMantiuk
This algorithm transforms image to contrast using gradients on all levels of gaussian pyramid,
transforms contrast values to HVS response and scales the response.
|
class |
TonemapReinhard
This is a global tonemapping operator that models human visual system.
|
Modifier and Type | Class and Description |
---|---|
class |
Plot2d
plot Plot function for Mat data
|
Modifier and Type | Class and Description |
---|---|
class |
GrayCodePattern
Class implementing the Gray-code pattern, based on CITE: UNDERWORLD.
|
class |
SinusoidalPattern
Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP)
and Fourier-assisted phase-shifting profilometry (FAPS) based on CITE: faps.
|
class |
StructuredLightPattern
Abstract base class for generating and decoding structured light patterns.
|
Modifier and Type | Class and Description |
---|---|
class |
ERFilter
Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm CITE: Neumann12.
|
Modifier and Type | Class and Description |
---|---|
class |
MultiTracker
This class is used to track multiple objects using the specified tracker algorithm.
|
class |
Tracker
Base abstract class for the long-term tracker:
|
class |
TrackerBoosting
the Boosting tracker
This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm.
|
class |
TrackerCSRT
the CSRT tracker
The implementation is based on CITE: Lukezic_IJCV2018 Discriminative Correlation Filter with Channel and Spatial Reliability
|
class |
TrackerGOTURN
the GOTURN (Generic Object Tracking Using Regression Networks) tracker
GOTURN (CITE: GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN).
|
class |
TrackerKCF
the KCF (Kernelized Correlation Filter) tracker
KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed.
|
class |
TrackerMedianFlow
the Median Flow tracker
Implementation of a paper CITE: MedianFlow .
|
class |
TrackerMIL
The MIL algorithm trains a classifier in an online manner to separate the object from the
background.
|
class |
TrackerMOSSE
the MOSSE (Minimum Output Sum of Squared %Error) tracker
The implementation is based on CITE: MOSSE Visual Object Tracking using Adaptive Correlation Filters
Note: this tracker works with grayscale images, if passed bgr ones, they will get converted internally.
|
class |
TrackerTLD
the TLD (Tracking, learning and detection) tracker
TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into
tracking, learning and detection.
|
Modifier and Type | Class and Description |
---|---|
class |
BackgroundSubtractor
Base class for background/foreground segmentation.
|
class |
BackgroundSubtractorKNN
K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
|
class |
BackgroundSubtractorMOG2
Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
|
class |
DenseOpticalFlow
Base class for dense optical flow algorithms
|
class |
DISOpticalFlow
DIS optical flow algorithm.
|
class |
FarnebackOpticalFlow
Class computing a dense optical flow using the Gunnar Farneback's algorithm.
|
class |
SparseOpticalFlow
Base interface for sparse optical flow algorithms.
|
class |
SparsePyrLKOpticalFlow
Class used for calculating a sparse optical flow.
|
class |
VariationalRefinement
Variational optical flow refinement
This class implements variational refinement of the input flow field, i.e.
|
Modifier and Type | Class and Description |
---|---|
class |
BoostDesc
Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in
CITE: Trzcinski13a and CITE: Trzcinski13b.
|
class |
BriefDescriptorExtractor
Class for computing BRIEF descriptors described in CITE: calon2010 .
|
class |
DAISY
Class implementing DAISY descriptor, described in CITE: Tola10
radius radius of the descriptor at the initial scale
q_radius amount of radial range division quantity
q_theta amount of angular range division quantity
q_hist amount of gradient orientations range division quantity
norm choose descriptors normalization type, where
DAISY::NRM_NONE will not do any normalization (default),
DAISY::NRM_PARTIAL mean that histograms are normalized independently for L2 norm equal to 1.0,
DAISY::NRM_FULL mean that descriptors are normalized for L2 norm equal to 1.0,
DAISY::NRM_SIFT mean that descriptors are normalized for L2 norm equal to 1.0 but no individual one is bigger than 0.154 as in SIFT
H optional 3x3 homography matrix used to warp the grid of daisy but sampling keypoints remains unwarped on image
interpolation switch to disable interpolation for speed improvement at minor quality loss
use_orientation sample patterns using keypoints orientation, disabled by default.
|
class |
FREAK
Class implementing the FREAK (*Fast Retina Keypoint*) keypoint descriptor, described in CITE: AOV12 .
|
class |
HarrisLaplaceFeatureDetector
Class implementing the Harris-Laplace feature detector as described in CITE: Mikolajczyk2004.
|
class |
LATCH
latch Class for computing the LATCH descriptor.
|
class |
LUCID
Class implementing the locally uniform comparison image descriptor, described in CITE: LUCID
An image descriptor that can be computed very fast, while being
about as robust as, for example, SURF or BRIEF.
|
class |
MSDDetector
Class implementing the MSD (*Maximal Self-Dissimilarity*) keypoint detector, described in CITE: Tombari14.
|
class |
PCTSignatures
Class implementing PCT (position-color-texture) signature extraction
as described in CITE: KrulisLS16.
|
class |
PCTSignaturesSQFD
Class implementing Signature Quadratic Form Distance (SQFD).
|
class |
SIFT
Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform
(SIFT) algorithm by D.
|
class |
StarDetector
The class implements the keypoint detector introduced by CITE: Agrawal08, synonym of StarDetector.
|
class |
SURF
Class for extracting Speeded Up Robust Features from an image CITE: Bay06 .
|
class |
VGG
Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end
using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in CITE: Simonyan14.
|
Modifier and Type | Class and Description |
---|---|
class |
AdaptiveManifoldFilter
Interface for Adaptive Manifold Filter realizations.
|
class |
ContourFitting
Class for ContourFitting algorithms.
|
class |
DisparityFilter
Main interface for all disparity map filters.
|
class |
DisparityWLSFilter
Disparity map filter based on Weighted Least Squares filter (in form of Fast Global Smoother that
is a lot faster than traditional Weighted Least Squares filter implementations) and optional use of
left-right-consistency-based confidence to refine the results in half-occlusions and uniform areas.
|
class |
DTFilter
Interface for realizations of Domain Transform filter.
|
class |
EdgeAwareInterpolator
Sparse match interpolation algorithm based on modified locally-weighted affine
estimator from CITE: Revaud2015 and Fast Global Smoother as post-processing filter.
|
class |
EdgeBoxes
Class implementing EdgeBoxes algorithm from CITE: ZitnickECCV14edgeBoxes :
|
class |
FastBilateralSolverFilter
Interface for implementations of Fast Bilateral Solver.
|
class |
FastGlobalSmootherFilter
Interface for implementations of Fast Global Smoother filter.
|
class |
FastLineDetector
Class implementing the FLD (Fast Line Detector) algorithm described
in CITE: Lee14 .
|
class |
GraphSegmentation
Graph Based Segmentation Algorithm.
|
class |
GuidedFilter
Interface for realizations of Guided Filter.
|
class |
RFFeatureGetter
Jun 17, 2014
|
class |
RICInterpolator
Sparse match interpolation algorithm based on modified piecewise locally-weighted affine
estimator called Robust Interpolation method of Correspondences or RIC from CITE: Hu2017 and Variational
and Fast Global Smoother as post-processing filter.
|
class |
RidgeDetectionFilter
Applies Ridge Detection Filter to an input image.
|
class |
SelectiveSearchSegmentation
Selective search segmentation algorithm
The class implements the algorithm described in CITE: uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategy
Strategie for the selective search segmentation algorithm
The class implements a generic stragery for the algorithm described in CITE: uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyColor
Color-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in CITE: uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyFill
Fill-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in CITE: uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyMultiple
Regroup multiple strategies for the selective search segmentation algorithm
|
class |
SelectiveSearchSegmentationStrategySize
Size-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in CITE: uijlings2013selective.
|
class |
SelectiveSearchSegmentationStrategyTexture
Texture-based strategy for the selective search segmentation algorithm
The class is implemented from the algorithm described in CITE: uijlings2013selective.
|
class |
SparseMatchInterpolator
Main interface for all filters, that take sparse matches as an
input and produce a dense per-pixel matching (optical flow) as an output.
|
class |
StructuredEdgeDetection
Class implementing edge detection algorithm from CITE: Dollar2013 :
|
class |
SuperpixelLSC
Class implementing the LSC (Linear Spectral Clustering) superpixels
algorithm described in CITE: LiCVPR2015LSC.
|
class |
SuperpixelSEEDS
Class implementing the SEEDS (Superpixels Extracted via Energy-Driven Sampling) superpixels
algorithm described in CITE: VBRV14 .
|
class |
SuperpixelSLIC
Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels
algorithm described in CITE: Achanta2012.
|
Modifier and Type | Class and Description |
---|---|
class |
GrayworldWB
Gray-world white balance algorithm
This algorithm scales the values of pixels based on a
gray-world assumption which states that the average of all channels
should result in a gray image.
|
class |
LearningBasedWB
More sophisticated learning-based automatic white balance algorithm.
|
class |
SimpleWB
A simple white balance algorithm that works by independently stretching
each of the input image channels to the specified range.
|
class |
TonemapDurand
This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter
and compresses contrast of the base layer thus preserving all the details.
|
class |
WhiteBalancer
The base class for auto white balance algorithms.
|
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