Base class for high-level OpenCV algorithms

Algorithm Information

The Base Class for Background/Foreground Segmentation. The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

The Base Class for Background/Foreground Segmentation. The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

The Base Class for Background/Foreground Segmentation. The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

The Base Class for Background/Foreground Segmentation. The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.

Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one.

Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one.

Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one.

Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one.

BRIEF Descriptor

BRISK implementation

Cascade classifier class for object detection.

Contrast Limited Adaptive Histogram Equalization

OpenCV Functions of C++ I/F (cv::xxx)

MLP model

Parameters of MLP training algorithm

Boosted tree classifier

Boosting training parameters

Weak tree classifier

Decision tree

Decision tree node

Decision tree training parameters

Decision tree node split

Decision tree node

K nearest neighbors classifier

Bayes classifier for normally distributed data

Training Parameters of Random Trees

Random Trees

Base class for statistical models in ML

Support Vector Machines

SVM training parameters

Class for generation of image features which are distributed densely and regularly over the image.

Abstract base class for computing descriptors for image keypoints.

struct for detection region of interest (ROI)

EM model (cv::EM)

Detects corners using FAST algorithm by E. Rosten

Abstract base class for 2D image feature detectors.

File Storage Node class

XML/YAML File Storage Class.

Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one.

FREAK implementation

Good Features To Track Detector

Information about the image topology for cv::findContours

HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector

Proxy datatype for passing Mat's and vector<>'s as input parameters

Proxy datatype for passing Mat's and vector<>'s as input parameters. Synonym for OutputArray.

Kalman filter. The class implements standard Kalman filter \url{http://en.wikipedia.org/wiki/Kalman_filter}. However, you can modify KalmanFilter::transitionMatrix, KalmanFilter::controlMatrix and KalmanFilter::measurementMatrix to get the extended Kalman filter functionality.

Find rectangular regions in the given image that are likely to contain objects and corresponding confidence levels

Structure contains the detection information.

OpenCV C++ n-dimensional dense array class (cv::Mat)

Mat column's indexer object

Mat column's indexer object

Mat Indexer

Mat row's indexer object

Mat row's indexer object

Type-specific abstract matrix

Matrix expression

Abstract definition of Mat indexer

A matrix whose element is 8UC1 (cv::Mat_<uchar>)

Matrix indexer

A matrix whose element is 8UC3 (cv::Mat_<cv::Vec3b>)

Matrix indexer

A matrix whose element is cv::DMatch (cv::Mat_<cv::Vec4f>)

Matrix indexer

A matrix whose element is 64FC1 (cv::Mat_<double>)

Matrix indexer

A matrix whose element is cv::Vec3d [CV_64FC3] (cv::Mat_<cv::Vec3d>)

Matrix indexer

A matrix whose element is 32FC1 (cv::Mat_<float>)

Matrix indexer

A matrix whose element is 32FC4 (cv::Mat_<cv::Vec4f>)

Matrix indexer

A matrix whose element is 32FC6 (cv::Mat_<cv::Vec6f>)

Matrix indexer

A matrix whose element is 32SC1 (cv::Mat_<int>)

Matrix indexer

A matrix whose element is 32SC1 (cv::Mat_<int>)

Matrix indexer

A matrix whose element is cv::Point [CV_32SC2] (cv::Mat_<cv::Point>)

A matrix whose element is cv::Point [CV_64FC2] (cv::Mat_<cv::Point2d>)

Matrix indexer

A matrix whose element is cv::Point [CV_32FC2] (cv::Mat_<cv::Point2f>)

Matrix indexer

A matrix whose element is cv::Point3d [CV_64FC3] (cv::Mat_<cv::Point3d>)

A matrix whose element is cv::Point3f [CV_32FC3] (cv::Mat_<cv::Point3f>)

A matrix whose element is cv::Point3i [CV_32SC3] (cv::Mat_<cv::Point3i>)

A matrix whose element is cv::Rect [CV_32SC4] (cv::Mat_<cv::Rect>)

A matrix whose element is 16SC1 (cv::Mat_<short>)

Matrix indexer

A matrix whose element is 16UC1 (cv::Mat_<ushort>)

Matrix indexer

Raster image moments

Maximal Stable Extremal Regions class

P/Invoke methods of OpenCV 2.x C++ interface

ORB implementation

Proxy datatype for passing Mat's and List<>'s as output parameters

Proxy datatype for passing Mat's and List<>'s as output parameters

Proxy datatype for passing Mat's and List<>'s as output parameters

Principal Component Analysis

Random Number Generator. The class implements RNG using Multiply-with-Carry algorithm.

Mersenne Twister random number generator

SIFT implementation.

Class for grouping object candidates, detected by Cascade Classifier, HOG etc. instance of the class is to be passed to cv::partition (see cxoperations.hpp)

Class for extracting blobs from an image.

SimpleBlobDetector parameters

Sparse matrix class.

Mat Indexer

Abstract definition of Mat indexer

The "Star" Detector

Class for computing stereo correspondence using the block matching algorithm.

Semi-Global Stereo Matching

High level image stitcher. It's possible to use this class without being aware of the entire stitching pipeline. However, to be able to achieve higher stitching stability and quality of the final images at least being familiar with the theory is recommended

Base class for Super Resolution algorithms.

Class for extracting Speeded Up Robust Features from an image.

Singular Value Decomposition class

Video capturing class

AVI Video File Writer

Wrapper of HighGUI window

A grid for the SVM algorithm.

Struct for matching: query descriptor index, train descriptor index, train image index and distance between descriptors.

Data structure for salient point detectors

Matrix data type (depth and number of channels)

float Range class

2-Tuple of byte (System.Byte)

2-Tuple of double (System.Double)

2-Tuple of float (System.Single)

2-Tuple of int (System.Int32)

2-Tuple of short (System.Int16)

2-Tuple of ushort (System.UInt16)

3-Tuple of byte (System.Byte)

3-Tuple of double (System.Double)

3-Tuple of float (System.Single)

3-Tuple of int (System.Int32)

3-Tuple of short (System.Int16)

3-Tuple of ushort (System.UInt16)

4-Tuple of byte (System.Byte)

4-Tuple of double (System.Double)

4-Tuple of float (System.Single)

4-Tuple of int (System.Int32)

4-Tuple of short (System.Int16)

4-Tuple of ushort (System.UInt16)

6-Tuple of byte (System.Byte)

6-Tuple of double (System.Double)

6-Tuple of float (System.Single)

6-Tuple of int (System.Int32)

6-Tuple of short (System.Int16)

4-Tuple of ushort (System.UInt16)

Abstract base class for computing descriptors for image keypoints.

cv::Algorithm parameter type

Splitting criteria, used to choose optimal splits during a weak tree construction

Data layout of decision tree

Flags for applyColorMap

Transformation flags for cv::dct

Transformation flags for cv::dft

Mask size for distance transform

Data layout of decision tree

Output string format of Mat.Dump()

The type of the mixture covariation matrices

The initial step the algorithm starts from

Method for solving a PnP problem:

GrabCut algorithm flags

diagonal type

MatrixDecomposition

Splitting criteria, used to choose optimal splits during a weak tree construction

The MLP training algorithm to use

The MLP training algorithm to use

cv::calcOpticalFlowPyrLK flags

cv::ORB score flags

cv::initWideAngleProjMap flags

Method for solving a PnP problem:

Status code

The kernel type of SVM

SVM params type

Type of SVM