Joe Verbout
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Data Structures
Here are the data structures with brief descriptions:
| _InputArray | This is the proxy class for passing read-only input arrays into OpenCV functions |
| _IplImage | The IplImage is taken from the Intel Image Processing Library, in which the format is native |
| _OutputArray | This type is very similar to InputArray except that it is used for input/output and output function parameters |
| Affine3< T > | Affine transform |
| AffineTransformer | Wrapper class for the OpenCV Affine Transformation algorithm |
| AgastFeatureDetector | Wrapping class for feature detection using the AGAST method |
| AKAZE | Class implementing the AKAZE keypoint detector and descriptor extractor, described in ANB13 |
| Algorithm | This is a base class for all more or less complex algorithms in OpenCV |
| AlignExposures | The base class for algorithms that align images of the same scene with different exposures |
| 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 |
| Allocator< _Tp > | |
| ANN_MLP | Artificial Neural Networks - Multi-Layer Perceptrons |
| Arrays | Wrapper for OpenGL Client-Side Vertex arrays |
| AutoBuffer< _Tp, fixed_size > | Automatically Allocated Buffer Class |
| BackgroundSubtractor | Base class for background/foreground segmentation |
| BackgroundSubtractorKNN | K-nearest neigbours - based Background/Foreground Segmentation Algorithm |
| BackgroundSubtractorMOG2 | Gaussian Mixture-based Background/Foreground Segmentation Algorithm |
| 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 |
| BFMatcher | Brute-force descriptor matcher |
| Blender | Base class for all blenders |
| BlocksGainCompensator | Exposure compensator which tries to remove exposure related artifacts by adjusting image block intensities, see UES01 for details |
| Boost | Boosted tree classifier derived from DTrees |
| BOWImgDescriptorExtractor | Class to compute an image descriptor using the *bag of visual words* |
| BOWKMeansTrainer | Kmeans -based class to train visual vocabulary using the *bag of visual words* approach |
| BOWTrainer | Abstract base class for training the *bag of visual words* vocabulary from a set of descriptors |
| BRISK | Class implementing the BRISK keypoint detector and descriptor extractor, described in LCS11 |
| Buffer | Smart pointer for OpenGL buffer object with reference counting |
| BundleAdjusterBase | Base class for all camera parameters refinement methods |
| 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 |
| BundleAdjusterReproj | Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection error squares |
| CalibrateCRF | The base class for camera response calibration algorithms |
| CalibrateDebevec | Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system |
| CalibrateRobertson | Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system |
| CameraParams | Describes camera parameters |
| CascadeClassifier | Cascade classifier class for object detection |
| ChiHistogramCostExtractor | An Chi based cost extraction |
| choose_policy< any > | Choosing the policy for an any type is illegal, but should never happen |
| CommandLineParser | Designed for command line parsing |
| Complex< _Tp > | A complex number class |
| CompositeIndex< Distance > | This index builds a kd-tree index and a k-means index and performs nearest neighbour search both indexes |
| CompositeIndexParams | Index parameters for the CompositeIndex |
| ConjGradSolver | This class is used to perform the non-linear non-constrained minimization of a function with known gradient, |
| CvAttrList | List of attributes |
| CvBox2D | |
| CvChainPtReader | Freeman chain reader state |
| CvConnectedComp | Connected component structure |
| CvConvexityDefect | Convexity defect |
| CvFileNode | Basic element of the file storage - scalar or collection: |
| CvFont | Font structure |
| CvHuMoments | Hu invariants |
| CvLineIterator | Line iterator state: |
| CvMat | Matrix elements are stored row by row |
| CvMatND | |
| CvMoments | Spatial and central moments |
| CvNArrayIterator | Matrix iterator: used for n-ary operations on dense arrays |
| CvRect | |
| CvScalar | |
| CvStringHashNode | All the keys (names) of elements in the readed file storage are stored in the hash to speed up the lookup operations: |
| CvTermCriteria | |
| CvType | Class for automatic module/RTTI data registration/unregistration |
| CvTypeInfo | Type information |
| CylindricalWarper | Cylindrical warper factory class |
| CylindricalWarper | Warper that maps an image onto the x\*x + z\*z = 1 cylinder |
| DataDepth< _Tp > | A helper class for cv::DataType |
| DataType< _Tp > | Template "trait" class for OpenCV primitive data types |
| DataType< Matx< _Tp, m, n > > | |
| DataType< Vec< _Tp, cn > > | |
| DescriptorMatcher::DescriptorCollection | Class to work with descriptors from several images as with one merged matrix |
| DescriptorMatcher | Abstract base class for matching keypoint descriptors |
| DetectionROI | Struct for detection region of interest (ROI) |
| DeviceInfo | Class providing functionality for querying the specified GPU properties |
| DMatch | Class for matching keypoint descriptors |
| DownhillSolver | This class is used to perform the non-linear non-constrained minimization of a function, |
| DTrees | The class represents a single decision tree or a collection of decision trees |
| DualTVL1OpticalFlow | "Dual TV L1" Optical Flow Algorithm |
| DynamicBitset | Class re-implementing the boost version of it This helps not depending on boost, it also does not do the bound checks and has a way to reset a block for speed |
| EM | The class implements the Expectation Maximization algorithm |
| EMDHistogramCostExtractor | An EMD based cost extraction |
| EMDL1HistogramCostExtractor | An EMD-L1 based cost extraction |
| Estimator | Rotation estimator base class |
| EventAccessor | Class that enables getting cudaEvent_t from cuda::Event |
| Exception | Class passed to an error |
| ExposureCompensator | Base class for all exposure compensators |
| FastFeatureDetector | Wrapping class for feature detection using the FAST method |
| FastMarchingMethod | Describes the Fast Marching Method implementation |
| FeatherBlender | Simple blender which mixes images at its borders |
| Feature2D | Abstract base class for 2D image feature detectors and descriptor extractors |
| FeaturesFinder | Feature finders base class |
| FeaturesMatcher | Feature matchers base class |
| FileNode | File Storage Node class |
| FileNodeIterator | Used to iterate through sequences and mappings |
| FileStorage | XML/YAML file storage class that encapsulates all the information necessary for writing or reading data to/from a file |
| FlannBasedMatcher | Flann-based descriptor matcher |
| Formatted | |
| Formatter | |
| MinProblemSolver::Function | Represents function being optimized |
| GainCompensator | Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities, see BL07 and WJ10 for details |
| GeneralizedHough | Finds arbitrary template in the grayscale image using Generalized Hough Transform |
| GeneralizedHoughBallard | Ballard, D.H |
| GeneralizedHoughGuil | Guil, N., González-Linares, J.M |
| GenericIndex< Distance > | The FLANN nearest neighbor index class |
| GFTTDetector | Wrapping class for feature detection using the goodFeaturesToTrack function |
| GpuMat | Base storage class for GPU memory with reference counting |
| GraphCutSeamFinder | Minimum graph cut-based seam estimator |
| GraphCutSeamFinderBase | Base class for all minimum graph-cut-based seam estimators |
| Hamming< T > | Hamming distance functor (pop count between two binary vectors, i.e |
| HammingLUT | Hamming distance functor - counts the bit differences between two strings - useful for the Brief descriptor bit count of A exclusive XOR'ed with B |
| HausdorffDistanceExtractor | A simple Hausdorff distance measure between shapes defined by contours |
| SparseMat::Hdr | Sparse matrix header |
| Heap< T > | Priority Queue Implementation |
| HierarchicalClusteringIndex< Distance > | Hierarchical index |
| HistogramCostExtractor | Abstract base class for histogram cost algorithms |
| HomographyBasedEstimator | Homography based rotation estimator |
| HostMem | Class with reference counting wrapping special memory type allocation functions from CUDA |
| ImageFeatures | Structure containing image keypoints and descriptors |
| ImageMotionEstimatorBase | Base class for global 2D motion estimation methods which take frames as input |
| Index_< T > | |
| IndexHeader | Structure representing the index header |
| KalmanFilter | Kalman filter class |
| KAZE | Class implementing the KAZE keypoint detector and descriptor extractor, described in ABD12 |
| KDTreeIndex< Distance > | Randomized kd-tree index |
| KDTreeSingleIndex< Distance > | Randomized kd-tree index |
| KeyPoint | Data structure for salient point detectors |
| KeypointBasedMotionEstimator | Describes a global 2D motion estimation method which uses keypoints detection and optical flow for matching |
| KeyPointsFilter | A class filters a vector of keypoints |
| KMeansIndex< Distance > | Hierarchical kmeans index |
| KNearest | The class implements K-Nearest Neighbors model |
| KNNRadiusUniqueResultSet< DistanceType > | Class that holds the k NN neighbors within a radius distance |
| KNNResultSet< DistanceType > | K-Nearest neighbour result set |
| KNNSimpleResultSet< DistanceType > | KNNSimpleResultSet does not ensure that the element it holds are unique |
| KNNUniqueResultSet< DistanceType > | Class that holds the k NN neighbors Faster than KNNResultSet as it uses a binary heap and does not maintain two arrays |
| L2< T > | Squared Euclidean distance functor, optimized version |
| L2_Simple< T > | Squared Euclidean distance functor |
| LDA | Linear Discriminant Analysis |
| LineIterator | Line iterator |
| LineSegmentDetector | Line segment detector class |
| LogisticRegression | Implements Logistic Regression classifier |
| LshIndex< Distance > | Randomized kd-tree index |
| LshStats | POD for stats about an LSH table |
| LshTable< ElementType > | Lsh hash table |
| Mat | N-dimensional dense array class |
| Mat_< _Tp > | Template matrix class derived from Mat |
| MatAllocator | Custom array allocator |
| MatchesInfo | Structure containing information about matches between two images |
| MatCommaInitializer_< _Tp > | Comma-separated Matrix Initializer |
| MatConstIterator_< _Tp > | Matrix read-only iterator |
| MatExpr | Matrix expression representation |
| MatIterator_< _Tp > | Matrix read-write iterator |
| Matrix< T > | Class that implements a simple rectangular matrix stored in a memory buffer and provides convenient matrix-like access using the [] operators |
| Matx< _Tp, m, n > | Template class for small matrices whose type and size are known at compilation time |
| MatxCommaInitializer< _Tp, m, n > | Comma-separated Matrix Initializer |
| MergeDebevec | The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response |
| MergeExposures | The base class algorithms that can merge exposure sequence to a single image |
| MergeMertens | Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids |
| MergeRobertson | The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response |
| MinProblemSolver | Basic interface for all solvers |
| Moments | Struct returned by cv::moments |
| MotionEstimatorBase | Base class for all global motion estimation methods |
| MotionEstimatorL1 | Describes a global 2D motion estimation method which minimizes L1 error |
| MotionEstimatorRansacL2 | Describes a robust RANSAC-based global 2D motion estimation method which minimizes L2 error |
| MSER | Maximally stable extremal region extractor |
| MultiBandBlender | Blender which uses multi-band blending algorithm (see BA83) |
| NAryMatIterator | N-ary multi-dimensional array iterator |
| NNIndex< Distance > | Nearest-neighbour index base class |
| SparseMat::Node | Sparse matrix node - element of a hash table |
| DTrees::Node | The class represents a decision tree node |
| NoExposureCompensator | Stub exposure compensator which does nothing |
| NormalBayesClassifier | Bayes classifier for normally distributed data |
| NormHistogramCostExtractor | A norm based cost extraction |
| NoSeamFinder | Stub seam estimator which does nothing |
| ORB | Class implementing the ORB (*oriented BRIEF*) keypoint detector and descriptor extractor |
| OrbFeaturesFinder | ORB features finder |
| PairwiseSeamFinder | Base class for all pairwise seam estimators |
| ParallelLoopBody | Base class for parallel data processors |
| ParamGrid | The structure represents the logarithmic grid range of statmodel parameters |
| PCA | Principal Component Analysis |
| PlaneWarper | Plane warper factory class |
| PlaneWarper | Warper that maps an image onto the z = 1 plane |
| Point3_< _Tp > | Template class for 3D points specified by its coordinates `x`, `y` and `z` |
| Point_< _Tp > | Template class for 2D points specified by its coordinates `x` and `y` |
| ProjectorBase | Base class for warping logic implementation |
| Ptr< T > | Template class for smart pointers with shared ownership |
| QtFont | QtFont available only for Qt |
| RadiusResultSet< DistanceType > | A result-set class used when performing a radius based search |
| RadiusUniqueResultSet< DistanceType > | Class that holds the radius nearest neighbors It is more accurate than RadiusResult as it is not limited in the number of neighbors |
| Range | Template class specifying a continuous subsequence (slice) of a sequence |
| RansacParams | Describes RANSAC method parameters |
| Rect_< _Tp > | Template class for 2D rectangles |
| RNG | Random Number Generator |
| RNG_MT19937 | Mersenne Twister random number generator |
| RotatedRect | The class represents rotated (i.e |
| RotationWarper | Rotation-only model image warper interface |
| RotationWarperBase< P > | Base class for rotation-based warper using a detail::ProjectorBase_ derived class |
| RTrees | The class implements the random forest predictor |
| SavedIndexParams | (Deprecated) Index parameters for creating a saved index |
| Scalar_< _Tp > | Template class for a 4-element vector derived from Vec |
| SeamFinder | Base class for a seam estimator |
| Seq< _Tp > | |
| SeqIterator< _Tp > | |
| ShapeContextDistanceExtractor | Implementation of the Shape Context descriptor and matching algorithm |
| ShapeDistanceExtractor | Abstract base class for shape distance algorithms |
| ShapeTransformer | Abstract base class for shape transformation algorithms |
| SimilarRects | Class for grouping object candidates, detected by Cascade Classifier, HOG etc |
| SimpleBlobDetector | Class for extracting blobs from an image |
| Size_< _Tp > | Template class for specifying the size of an image or rectangle |
| SparseMat | The class SparseMat represents multi-dimensional sparse numerical arrays |
| SparseMat_< _Tp > | Template sparse n-dimensional array class derived from SparseMat |
| SparseMatConstIterator | Read-Only Sparse Matrix Iterator |
| SparseMatConstIterator_< _Tp > | Template Read-Only Sparse Matrix Iterator Class |
| SparseMatIterator | Read-write Sparse Matrix Iterator |
| SparseMatIterator_< _Tp > | Template Read-Write Sparse Matrix Iterator Class |
| SphericalWarper | Spherical warper factory class |
| SphericalWarper | Warper that maps an image onto the unit sphere located at the origin |
| DTrees::Split | The class represents split in a decision tree |
| StartStopTimer | A start-stop timer class |
| StatModel | Base class for statistical models in OpenCV ML |
| StereoBM | Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K |
| StereoMatcher | The base class for stereo correspondence algorithms |
| StereoSGBM | The class implements the modified H |
| Stitcher | High level image stitcher |
| Stream | This class encapsulates a queue of asynchronous calls |
| StreamAccessor | Class that enables getting cudaStream_t from cuda::Stream |
| SuperResolution | Base class for Super Resolution algorithms |
| SurfFeaturesFinder | SURF features finder |
| SVD | Singular Value Decomposition |
| SVM | Support Vector Machines |
| TargetArchs | Class providing a set of static methods to check what NVIDIA\* card architecture the CUDA module was built for |
| TermCriteria | The class defining termination criteria for iterative algorithms |
| Texture2D | Smart pointer for OpenGL 2D texture memory with reference counting |
| ThinPlateSplineShapeTransformer | Definition of the transformation |
| Tonemap | Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range |
| TonemapDrago | Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain |
| 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 |
| 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 |
| TonemapReinhard | This is a global tonemapping operator that models human visual system |
| TrainData | Class encapsulating training data |
| UMat | |
| UniqueRandom | Random number generator that returns a distinct number from the [0,n) interval each time |
| UniqueResultSet< DistanceType > | Class that holds the k NN neighbors Faster than KNNResultSet as it uses a binary heap and does not maintain two arrays |
| Vec< _Tp, cn > | Template class for short numerical vectors, a partial case of Matx |
| VecCommaInitializer< _Tp, m > | Comma-separated Vec Initializer |
| VideoCapture | Class for video capturing from video files, image sequences or cameras |
| VideoWriter | Video writer class |
| VoronoiSeamFinder | Voronoi diagram-based seam estimator |
| WarperCreator | Image warper factories base class |
| WImage< T > | Image class which provides a thin layer around an IplImage |
| WImageBuffer< T > | Image class which owns the data, so it can be allocated and is always freed |
| WImageBufferC< T, C > | Like a WImageBuffer class but when the number of channels is known at compile time |
| WImageC< T, C > | Image class when both the pixel type and number of channels are known at compile time |
| WImageView< T > | View into an image class which allows treating a subimage as an image or treating external data as an image |
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