Board of markers  C CharucoBoard ChArUco board Specific class for ChArUco boards. A ChArUco board is a planar board where the markers are placed inside the white squares of a chessboard. The benefits of ChArUco boards is that they provide both, ArUco markers versatility and chessboard corner precision, which is important for calibration and pose estimation. This class also allows the easy creation and drawing of ChArUco boards  C DetectorParameters Parameters for the detectMarker process:  C Dictionary Dictionary/Set of markers. It contains the inner codification  C GridBoard Planar board with grid arrangement of markers More common type of board. All markers are placed in the same plane in a grid arrangment. The board can be drawn using drawPlanarBoard() function (  C BackgroundSubtractorCNT Background subtraction based on counting  C BackgroundSubtractorGMG Background Subtractor module based on the algorithm given in [69] C 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  C BackgroundSubtractorLSBP Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [74] C BackgroundSubtractorLSBPDesc This is for calculation of the LSBP descriptors  C BackgroundSubtractorMOG Gaussian Mixture-based Background/Foreground Segmentation Algorithm C SyntheticSequenceGenerator Synthetic frame sequence generator for testing background subtraction algorithms  C Retina Class which allows the Gipsa/Listic Labs model to be used with OpenCV  C RetinaFastToneMapping Wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV Retina model parameters structure  C IplMagnoParameters Inner Plexiform Layer Magnocellular channel (IplMagno)  C OPLandIplParvoParameters Outer Plexiform Layer (OPL) and Inner Plexiform Layer Parvocellular (IplParvo) parameters  C SegmentationParameters Parameter structure that stores the transient events detector setup parameters  C TransientAreasSegmentationModule Class which provides a transient/moving areas segmentation module  C Bridge Type conversion class for converting OpenCV and native C++ types  C CustomPattern C descriptorExtractor Caffe based 3D images descriptor. A class to extract features from an image. The so obtained descriptors can be used for classification and pose estimation goals [207] C icoSphere Icosohedron based camera view data generator. The class create some sphere views of camera towards a 3D object meshed from .ply files [83] C BackgroundSubtractorFGD The class discriminates between foreground and background pixels by building and maintaining a model of the background  C BackgroundSubtractorGMG Background/Foreground Segmentation Algorithm C BackgroundSubtractorMOG Gaussian Mixture-based Background/Foreground Segmentation Algorithm C BackgroundSubtractorMOG2 Gaussian Mixture-based Background/Foreground Segmentation Algorithm C BroxOpticalFlow Class computing the optical flow for two images using Brox et al Optical Flow algorithm ( [26] )  C BufferPool BufferPool for use with CUDA streams  C CannyEdgeDetector Base class for Canny Edge Detector . :  C CascadeClassifier Cascade classifier class used for object detection. Supports HAAR and LBP cascades. :  C CLAHE Base class for Contrast Limited Adaptive Histogram Equalization. :  C Convolution Base class for convolution (or cross-correlation) operator. :  C CornernessCriteria Base class for Cornerness Criteria computation. :  C CornersDetector Base class for Corners Detector . :  C DenseOpticalFlow Base interface for dense optical flow algorithms  C DensePyrLKOpticalFlow Class used for calculating a dense optical flow  C DescriptorMatcher Abstract base class for matching keypoint descriptors  C DeviceInfo Class providing functionality for querying the specified GPU properties  C DFT Base class for DFT operator as a cv::Algorithm . :  C DisparityBilateralFilter Class refining a disparity map using joint bilateral filtering. :  C Event C EventAccessor Class that enables getting cudaEvent_t from cuda::Event C FarnebackOpticalFlow Class computing a dense optical flow using the Gunnar Farneback's algorithm  C FastFeatureDetector Wrapping class for feature detection using the FAST method  C FastOpticalFlowBM C Feature2DAsync Abstract base class for CUDA asynchronous 2D image feature detectors and descriptor extractors  C FGDParams C Filter Common interface for all CUDA filters :  ▼C GpuMat Base storage class for GPU memory with reference counting  C Allocator C HOG The class implements Histogram of Oriented Gradients ( [37] ) object detector  C HostMem Class with reference counting wrapping special memory type allocation functions from CUDA  C HoughCirclesDetector Base class for circles detector algorithm. :  C HoughLinesDetector Base class for lines detector algorithm. :  C HoughSegmentDetector Base class for line segments detector algorithm. :  C ImagePyramid C LookUpTable Base class for transform using lookup table  C OpticalFlowDual_TVL1 Implementation of the Zach, Pock and Bischof Dual TV-L1 Optical Flow method  C ORB Class implementing the ORB ( oriented BRIEF ) keypoint detector and descriptor extractor  C SparseOpticalFlow Base interface for sparse optical flow algorithms  C SparsePyrLKOpticalFlow Class used for calculating a sparse optical flow  C StereoBeliefPropagation Class computing stereo correspondence using the belief propagation algorithm. :  C StereoBM Class computing stereo correspondence (disparity map) using the block matching algorithm. :  C StereoConstantSpaceBP Class computing stereo correspondence using the constant space belief propagation algorithm. :  C Stream This class encapsulates a queue of asynchronous calls  C StreamAccessor Class that enables getting cudaStream_t from cuda::Stream C SURF_CUDA Class used for extracting Speeded Up Robust Features (SURF) from an image. :  C TargetArchs Class providing a set of static methods to check what NVIDIA* card architecture the CUDA module was built for  C TemplateMatching Base class for Template Matching. :  C EncoderCallBack Callbacks for CUDA video encoder  C EncoderParams Different parameters for CUDA video encoder  C FormatInfo Struct providing information about video file format. :  C RawVideoSource Interface for video demultiplexing. :  C VideoReader Video reader interface  C VideoWriter Video writer interface  ▼N functional_detail C FloatType ▼N vec_math_detail C SatCastHelper C SatCastHelper< 1, VecD > C SatCastHelper< 2, VecD > C SatCastHelper< 3, VecD > C SatCastHelper< 4, VecD > C abs_func C abs_func< double > C abs_func< float > C abs_func< schar > C abs_func< short > C abs_func< uchar > C abs_func< uint > C abs_func< ushort > C absdiff_func C acos_func C acos_func< double > C acos_func< float > C acos_func< schar > C acos_func< short > C acos_func< uchar > C acos_func< uint > C acos_func< ushort > C acosh_func C acosh_func< double > C acosh_func< float > C acosh_func< schar > C acosh_func< short > C acosh_func< uchar > C acosh_func< uint > C acosh_func< ushort > C AffineMapPtr C AffineMapPtrSz C ArrayWrapper C asin_func C asin_func< double > C asin_func< float > C asin_func< schar > C asin_func< short > C asin_func< uchar > C asin_func< uint > C asin_func< ushort > C asinh_func C asinh_func< double > C asinh_func< float > C asinh_func< schar > C asinh_func< short > C asinh_func< uchar > C asinh_func< uint > C asinh_func< ushort > C atan2_func C atan2_func< double > C atan2_func< float > C atan2_func< schar > C atan2_func< short > C atan2_func< uchar > C atan2_func< uint > C atan2_func< ushort > C atan_func C atan_func< double > C atan_func< float > C atan_func< schar > C atan_func< short > C atan_func< uchar > C atan_func< uint > C atan_func< ushort > C atanh_func C atanh_func< double > C atanh_func< float > C atanh_func< schar > C atanh_func< short > C atanh_func< uchar > C atanh_func< uint > C atanh_func< ushort > ▼C Avg C rebind C BGR_to_BGRA_func C BGR_to_GRAY_func C BGR_to_HLS4_FULL_func C BGR_to_HLS4_FULL_func< float > C BGR_to_HLS4_func C BGR_to_HLS4_func< float > C BGR_to_HLS_FULL_func C BGR_to_HLS_FULL_func< float > C BGR_to_HLS_func C BGR_to_HLS_func< float > C BGR_to_HSV4_FULL_func C BGR_to_HSV4_FULL_func< float > C BGR_to_HSV4_func C BGR_to_HSV4_func< float > C BGR_to_HSV_FULL_func C BGR_to_HSV_FULL_func< float > C BGR_to_HSV_func C BGR_to_HSV_func< float > C BGR_to_Lab4_func C BGR_to_Lab_func C BGR_to_Luv4_func C BGR_to_Luv_func C BGR_to_RGB_func C BGR_to_RGBA_func C BGR_to_XYZ4_func C BGR_to_XYZ_func C BGR_to_YCrCb4_func C BGR_to_YCrCb_func C BGR_to_YUV4_func C BGR_to_YUV_func C BGRA_to_BGR_func C BGRA_to_GRAY_func C BGRA_to_HLS4_FULL_func C BGRA_to_HLS4_FULL_func< float > C BGRA_to_HLS4_func C BGRA_to_HLS4_func< float > C BGRA_to_HLS_FULL_func C BGRA_to_HLS_FULL_func< float > C BGRA_to_HLS_func C BGRA_to_HLS_func< float > C BGRA_to_HSV4_FULL_func C BGRA_to_HSV4_FULL_func< float > C BGRA_to_HSV4_func C BGRA_to_HSV4_func< float > C BGRA_to_HSV_FULL_func C BGRA_to_HSV_FULL_func< float > C BGRA_to_HSV_func C BGRA_to_HSV_func< float > C BGRA_to_Lab4_func C BGRA_to_Lab_func C BGRA_to_Luv4_func C BGRA_to_Luv_func C BGRA_to_RGB_func C BGRA_to_RGBA_func C BGRA_to_XYZ4_func C BGRA_to_XYZ_func C BGRA_to_YCrCb4_func C BGRA_to_YCrCb_func C BGRA_to_YUV4_func C BGRA_to_YUV_func C binary_function C BinaryNegate C BinaryTransformPtr C BinaryTransformPtrSz C BinaryTupleAdapter C Binder1st C Binder2nd C bit_and C bit_lshift C bit_not C bit_or C bit_rshift C bit_xor C Block C BrdBase C BrdConstant C BrdReflect C BrdReflect101 C BrdReplicate C BrdWrap C CommonAreaInterPtr C CommonAreaInterPtrSz C ConstantPtr C ConstantPtrSz C ConvertTuple C cos_func C cos_func< double > C cos_func< float > C cos_func< schar > C cos_func< short > C cos_func< uchar > C cos_func< uint > C cos_func< ushort > C cosh_func C cosh_func< double > C cosh_func< float > C cosh_func< schar > C cosh_func< short > C cosh_func< uchar > C cosh_func< uint > C cosh_func< ushort > C CountNonZeroExprBody C CubicInterPtr C CubicInterPtrSz C DefaultCopyPolicy C DefaultGlobReducePolicy C DefaultHistogramPolicy C DefaultReduceToVecPolicy C DefaultSplitMergePolicy C DefaultTransformPolicy C DefaultTransposePolicy C DerivXPtr C DerivXPtrSz C DerivYPtr C DerivYPtrSz C direction_func C DisableIf C DisableIf< false, T > C divides C DynamicSharedMem C DynamicSharedMem< double > C EnableIf C EnableIf< true, T > C equal_to C exp10_func C exp10_func< double > C exp10_func< float > C exp10_func< schar > C exp10_func< short > C exp10_func< uchar > C exp10_func< uint > C exp10_func< ushort > C exp2_func C exp2_func< double > C exp2_func< float > C exp2_func< schar > C exp2_func< short > C exp2_func< uchar > C exp2_func< uint > C exp2_func< ushort > C exp_func C exp_func< double > C exp_func< float > C exp_func< schar > C exp_func< short > C exp_func< uchar > C exp_func< uint > C exp_func< ushort > C Expr C FindMaxValExprBody C FindMinMaxValExprBody C FindMinValExprBody C GlobPtr Structure similar to cv::cudev::GlobPtrSz but containing only a pointer and row step  C GlobPtrSz Lightweight class encapsulating pitched memory on a GPU and passed to nvcc-compiled code (CUDA kernels)  C GpuMat_ C GRAY_to_BGR_func C GRAY_to_BGRA_func C greater C greater_equal C HistogramBody C HLS4_to_BGR_FULL_func C HLS4_to_BGR_FULL_func< float > C HLS4_to_BGR_func C HLS4_to_BGR_func< float > C HLS4_to_BGRA_FULL_func C HLS4_to_BGRA_FULL_func< float > C HLS4_to_BGRA_func C HLS4_to_BGRA_func< float > C HLS4_to_RGB_FULL_func C HLS4_to_RGB_FULL_func< float > C HLS4_to_RGB_func C HLS4_to_RGB_func< float > C HLS4_to_RGBA_FULL_func C HLS4_to_RGBA_FULL_func< float > C HLS4_to_RGBA_func C HLS4_to_RGBA_func< float > C HLS_to_BGR_FULL_func C HLS_to_BGR_FULL_func< float > C HLS_to_BGR_func C HLS_to_BGR_func< float > C HLS_to_BGRA_FULL_func C HLS_to_BGRA_FULL_func< float > C HLS_to_BGRA_func C HLS_to_BGRA_func< float > C HLS_to_RGB_FULL_func C HLS_to_RGB_FULL_func< float > C HLS_to_RGB_func C HLS_to_RGB_func< float > C HLS_to_RGBA_FULL_func C HLS_to_RGBA_FULL_func< float > C HLS_to_RGBA_func C HLS_to_RGBA_func< float > C HSV4_to_BGR_FULL_func C HSV4_to_BGR_FULL_func< float > C HSV4_to_BGR_func C HSV4_to_BGR_func< float > C HSV4_to_BGRA_FULL_func C HSV4_to_BGRA_FULL_func< float > C HSV4_to_BGRA_func C HSV4_to_BGRA_func< float > C HSV4_to_RGB_FULL_func C HSV4_to_RGB_FULL_func< float > C HSV4_to_RGB_func C HSV4_to_RGB_func< float > C HSV4_to_RGBA_FULL_func C HSV4_to_RGBA_FULL_func< float > C HSV4_to_RGBA_func C HSV4_to_RGBA_func< float > C HSV_to_BGR_FULL_func C HSV_to_BGR_FULL_func< float > C HSV_to_BGR_func C HSV_to_BGR_func< float > C HSV_to_BGRA_FULL_func C HSV_to_BGRA_FULL_func< float > C HSV_to_BGRA_func C HSV_to_BGRA_func< float > C HSV_to_RGB_FULL_func C HSV_to_RGB_FULL_func< float > C HSV_to_RGB_func C HSV_to_RGB_func< float > C HSV_to_RGBA_FULL_func C HSV_to_RGBA_FULL_func< float > C HSV_to_RGBA_func C HSV_to_RGBA_func< float > C hypot_func C hypot_func< double > C hypot_func< float > C hypot_func< schar > C hypot_func< short > C hypot_func< uchar > C hypot_func< uint > C hypot_func< ushort > C identity C Int2Type C IntegerAreaInterPtr C IntegerAreaInterPtrSz C IntegralBody ▼C IsBinaryFunction C IsPowerOf2 ▼C IsUnaryFunction C Lab4_to_BGR_func C Lab4_to_BGRA_func C Lab4_to_LBGR_func C Lab4_to_LBGRA_func C Lab4_to_LRGB_func C Lab4_to_LRGBA_func C Lab4_to_RGB_func C Lab4_to_RGBA_func C Lab_to_BGR_func C Lab_to_BGRA_func C Lab_to_LBGR_func C Lab_to_LBGRA_func C Lab_to_LRGB_func C Lab_to_LRGBA_func C Lab_to_RGB_func C Lab_to_RGBA_func C LaplacianPtr C LaplacianPtr< 1, SrcPtr > C LaplacianPtr< 3, SrcPtr > C LaplacianPtrSz C LargerType C LBGR_to_Lab4_func C LBGR_to_Lab_func C LBGR_to_Luv4_func C LBGR_to_Luv_func C LBGRA_to_Lab4_func C LBGRA_to_Lab_func C LBGRA_to_Luv4_func C LBGRA_to_Luv_func C less C less_equal C LinearInterPtr C LinearInterPtrSz C log10_func C log10_func< double > C log10_func< float > C log10_func< schar > C log10_func< short > C log10_func< uchar > C log10_func< uint > C log10_func< ushort > C Log2 C Log2< N, 0, COUNT > C log2_func C log2_func< double > C log2_func< float > C log2_func< schar > C log2_func< short > C log2_func< uchar > C log2_func< uint > C log2_func< ushort > C log_func C log_func< double > C log_func< float > C log_func< schar > C log_func< short > C log_func< uchar > C log_func< uint > C log_func< ushort > C logical_and C logical_not C logical_or C LRGB_to_Lab4_func C LRGB_to_Lab_func C LRGB_to_Luv4_func C LRGB_to_Luv_func C LRGBA_to_Lab4_func C LRGBA_to_Lab_func C LRGBA_to_Luv4_func C LRGBA_to_Luv_func C LutPtr C LutPtrSz C Luv4_to_BGR_func C Luv4_to_BGRA_func C Luv4_to_LBGR_func C Luv4_to_LBGRA_func C Luv4_to_LRGB_func C Luv4_to_LRGBA_func C Luv4_to_RGB_func C Luv4_to_RGBA_func C Luv_to_BGR_func C Luv_to_BGRA_func C Luv_to_LBGR_func C Luv_to_LBGRA_func C Luv_to_LRGB_func C Luv_to_LRGBA_func C Luv_to_RGB_func C Luv_to_RGBA_func C magnitude_func C magnitude_sqr_func C MakeVec C MakeVec< bool, 1 > C MakeVec< bool, 2 > C MakeVec< bool, 3 > C MakeVec< bool, 4 > C MakeVec< double, 1 > C MakeVec< double, 2 > C MakeVec< double, 3 > C MakeVec< double, 4 > C MakeVec< float, 1 > C MakeVec< float, 2 > C MakeVec< float, 3 > C MakeVec< float, 4 > C MakeVec< schar, 1 > C MakeVec< schar, 2 > C MakeVec< schar, 3 > C MakeVec< schar, 4 > C MakeVec< short, 1 > C MakeVec< short, 2 > C MakeVec< short, 3 > C MakeVec< short, 4 > C MakeVec< uchar, 1 > C MakeVec< uchar, 2 > C MakeVec< uchar, 3 > C MakeVec< uchar, 4 > C MakeVec< uint, 1 > C MakeVec< uint, 2 > C MakeVec< uint, 3 > C MakeVec< uint, 4 > C MakeVec< ushort, 1 > C MakeVec< ushort, 2 > C MakeVec< ushort, 3 > C MakeVec< ushort, 4 > ▼C Max C rebind C maximum C maximum< double > C maximum< float > C maximum< schar > C maximum< short > C maximum< uchar > C maximum< uint > C maximum< ushort > ▼C Min C rebind C minimum C minimum< double > C minimum< float > C minimum< schar > C minimum< short > C minimum< uchar > C minimum< uint > C minimum< ushort > C minus C modulus C multiplies C NearestInterPtr C NearestInterPtrSz C negate C NormHamming C NormL1 C NormL1< float > C NormL2 C not_equal_to C NullType C numeric_limits C numeric_limits< bool > C numeric_limits< double > C numeric_limits< float > C numeric_limits< schar > C numeric_limits< short > C numeric_limits< uchar > C numeric_limits< uint > C numeric_limits< ushort > C PerspectiveMapPtr C PerspectiveMapPtrSz C plus C pow_func C pow_func< double > C project1st C project2nd C PtrTraits C PtrTraits< AffineMapPtrSz > C PtrTraits< BinaryTransformPtrSz< Src1Ptr, Src2Ptr, Op > > C PtrTraits< CommonAreaInterPtrSz< SrcPtr > > C PtrTraits< ConstantPtrSz< T > > C PtrTraits< CubicInterPtrSz< SrcPtr > > C PtrTraits< DerivXPtrSz< SrcPtr > > C PtrTraits< DerivYPtrSz< SrcPtr > > C PtrTraits< Expr< Body > > C PtrTraits< GlobPtrSz< T > > C PtrTraits< GpuMat_< T > > C PtrTraits< IntegerAreaInterPtrSz< SrcPtr > > C PtrTraits< LaplacianPtrSz< ksize, SrcPtr > > C PtrTraits< LinearInterPtrSz< SrcPtr > > C PtrTraits< LutPtrSz< SrcPtr, TablePtr > > C PtrTraits< NearestInterPtrSz< SrcPtr > > C PtrTraits< PerspectiveMapPtrSz > C PtrTraits< RemapPtr1Sz< SrcPtr, MapPtr > > C PtrTraits< RemapPtr2Sz< SrcPtr, MapXPtr, MapYPtr > > C PtrTraits< ResizePtrSz< SrcPtr > > C PtrTraits< ScharrXPtrSz< SrcPtr > > C PtrTraits< ScharrYPtrSz< SrcPtr > > C PtrTraits< SingleMaskChannelsSz< MaskPtr > > C PtrTraits< SobelXPtrSz< SrcPtr > > C PtrTraits< SobelYPtrSz< SrcPtr > > C PtrTraits< Texture< T > > C PtrTraits< UnaryTransformPtrSz< SrcPtr, Op > > C PtrTraits< ZipPtrSz< PtrTuple > > C PtrTraitsBase C PyrDownBody C PyrUpBody C ReduceToColumnBody C ReduceToRowBody C RemapPtr1 C RemapPtr1Sz C RemapPtr2 C RemapPtr2Sz C ResizePtr C ResizePtrSz C RGB_to_GRAY_func C RGB_to_HLS4_FULL_func C RGB_to_HLS4_FULL_func< float > C RGB_to_HLS4_func C RGB_to_HLS4_func< float > C RGB_to_HLS_FULL_func C RGB_to_HLS_FULL_func< float > C RGB_to_HLS_func C RGB_to_HLS_func< float > C RGB_to_HSV4_FULL_func C RGB_to_HSV4_FULL_func< float > C RGB_to_HSV4_func C RGB_to_HSV4_func< float > C RGB_to_HSV_FULL_func C RGB_to_HSV_FULL_func< float > C RGB_to_HSV_func C RGB_to_HSV_func< float > C RGB_to_Lab4_func C RGB_to_Lab_func C RGB_to_Luv4_func C RGB_to_Luv_func C RGB_to_XYZ4_func C RGB_to_XYZ_func C RGB_to_YCrCb4_func C RGB_to_YCrCb_func C RGB_to_YUV4_func C RGB_to_YUV_func C RGBA_to_GRAY_func C RGBA_to_HLS4_FULL_func C RGBA_to_HLS4_FULL_func< float > C RGBA_to_HLS4_func C RGBA_to_HLS4_func< float > C RGBA_to_HLS_FULL_func C RGBA_to_HLS_FULL_func< float > C RGBA_to_HLS_func C RGBA_to_HLS_func< float > C RGBA_to_HSV4_FULL_func C RGBA_to_HSV4_FULL_func< float > C RGBA_to_HSV4_func C RGBA_to_HSV4_func< float > C RGBA_to_HSV_FULL_func C RGBA_to_HSV_FULL_func< float > C RGBA_to_HSV_func C RGBA_to_HSV_func< float > C RGBA_to_Lab4_func C RGBA_to_Lab_func C RGBA_to_Luv4_func C RGBA_to_Luv_func C RGBA_to_XYZ4_func C RGBA_to_XYZ_func C RGBA_to_YCrCb4_func C RGBA_to_YCrCb_func C RGBA_to_YUV4_func C RGBA_to_YUV_func C saturate_cast_fp16_func C saturate_cast_fp16_func< float, short > C saturate_cast_fp16_func< short, float > C saturate_cast_func C ScharrXPtr C ScharrXPtrSz C ScharrYPtr C ScharrYPtrSz C SelectIf C SelectIf< false, ThenType, ElseType > C sin_func C sin_func< double > C sin_func< float > C sin_func< schar > C sin_func< short > C sin_func< uchar > C sin_func< uint > C sin_func< ushort > C SingleMaskChannels C SingleMaskChannelsSz C sinh_func C sinh_func< double > C sinh_func< float > C sinh_func< schar > C sinh_func< short > C sinh_func< uchar > C sinh_func< uint > C sinh_func< ushort > C SobelXPtr C SobelXPtrSz C SobelYPtr C SobelYPtrSz C sqr_func C sqrt_func C sqrt_func< double > C sqrt_func< float > C sqrt_func< schar > C sqrt_func< short > C sqrt_func< uchar > C sqrt_func< uint > C sqrt_func< ushort > ▼C Sum C rebind C SumExprBody C tan_func C tan_func< double > C tan_func< float > C tan_func< schar > C tan_func< short > C tan_func< uchar > C tan_func< uint > C tan_func< ushort > C tanh_func C tanh_func< double > C tanh_func< float > C tanh_func< schar > C tanh_func< short > C tanh_func< uchar > C tanh_func< uint > C tanh_func< ushort > C Texture C TexturePtr C ThreshBinaryFunc C ThreshBinaryInvFunc C ThreshToZeroFunc C ThreshToZeroInvFunc C ThreshTruncFunc C TransposeBody C TupleTraits C TupleTraits< tuple< P0, P1, P2, P3, P4, P5, P6, P7, P8, P9 > > C TypesEquals C TypesEquals< A, A > C TypeTraits C unary_function C UnaryNegate C UnaryTransformPtr C UnaryTransformPtrSz C UnaryTupleAdapter C VecTraits C VecTraits< char1 > C VecTraits< char2 > C VecTraits< char3 > C VecTraits< char4 > C VecTraits< double > C VecTraits< double1 > C VecTraits< double2 > C VecTraits< double3 > C VecTraits< double4 > C VecTraits< float > C VecTraits< float1 > C VecTraits< float2 > C VecTraits< float3 > C VecTraits< float4 > C VecTraits< int1 > C VecTraits< int2 > C VecTraits< int3 > C VecTraits< int4 > C VecTraits< schar > C VecTraits< short > C VecTraits< short1 > C VecTraits< short2 > C VecTraits< short3 > C VecTraits< short4 > C VecTraits< uchar > C VecTraits< uchar1 > C VecTraits< uchar2 > C VecTraits< uchar3 > C VecTraits< uchar4 > C VecTraits< uint > C VecTraits< uint1 > C VecTraits< uint2 > C VecTraits< uint3 > C VecTraits< uint4 > C VecTraits< ushort > C VecTraits< ushort1 > C VecTraits< ushort2 > C VecTraits< ushort3 > C VecTraits< ushort4 > C Warp C WithOutMask C XYZ4_to_BGR_func C XYZ4_to_BGRA_func C XYZ4_to_RGB_func C XYZ4_to_RGBA_func C XYZ_to_BGR_func C XYZ_to_BGRA_func C XYZ_to_RGB_func C XYZ_to_RGBA_func C YCrCb4_to_BGR_func C YCrCb4_to_BGRA_func C YCrCb4_to_RGB_func C YCrCb4_to_RGBA_func C YCrCb_to_BGR_func C YCrCb_to_BGRA_func C YCrCb_to_RGB_func C YCrCb_to_RGBA_func C YUV4_to_BGR_func C YUV4_to_BGRA_func C YUV4_to_RGB_func C YUV4_to_RGBA_func C YUV_to_BGR_func C YUV_to_BGRA_func C YUV_to_RGB_func C YUV_to_RGBA_func C ZipPtr C ZipPtr< tuple< Ptr0, Ptr1 > > C ZipPtr< tuple< Ptr0, Ptr1, Ptr2 > > C ZipPtr< tuple< Ptr0, Ptr1, Ptr2, Ptr3 > > C ZipPtrSz C AR_hmdb C AR_hmdbObj C AR_sports C AR_sportsObj C cameraParam C cameraPos C Dataset C FR_adience C FR_adienceObj C FR_lfw C FR_lfwObj C GR_chalearn C GR_chalearnObj C GR_skig C GR_skigObj C groundTruth C HPE_humaneva C HPE_humanevaObj C HPE_parse C HPE_parseObj C IR_affine C IR_affineObj C IR_robot C IR_robotObj C IS_bsds C IS_bsdsObj C IS_weizmann C IS_weizmannObj C join C MSM_epfl C MSM_epflObj C MSM_middlebury C MSM_middleburyObj C Object C OR_imagenet C OR_imagenetObj C OR_mnist C OR_mnistObj C OR_pascal C OR_pascalObj C OR_sun C OR_sunObj C PascalObj C PascalPart C PD_caltech C PD_caltechObj C PD_inria C PD_inriaObj C pose C skeleton C SLAM_kitti C SLAM_kittiObj C SLAM_tumindoor C SLAM_tumindoorObj C tag C TR_chars C TR_charsObj C TR_icdar C TR_icdarObj C TR_svt C TR_svtObj C TRACK_alov C TRACK_alovObj C TRACK_vot C TRACK_votObj C word C AffineBasedEstimator Affine transformation based estimator  C 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  C AffineWarper Affine warper that uses rotations and translations  C AKAZEFeaturesFinder AKAZE features finder. :  C 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  C BestOf2NearestRangeMatcher C Blender Base class for all blenders  C BlocksGainCompensator Exposure compensator which tries to remove exposure related artifacts by adjusting image block intensities, see [189] for details  C 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  C 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  C BundleAdjusterBase Base class for all camera parameters refinement methods  C 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. :  C BundleAdjusterReproj Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection error squares  C CameraParams Describes camera parameters  C CompressedRectilinearPortraitProjector C CompressedRectilinearPortraitWarper C CompressedRectilinearProjector C CompressedRectilinearWarper C CylindricalPortraitProjector C CylindricalPortraitWarper C CylindricalProjector C CylindricalWarper Warper that maps an image onto the x*x + z*z = 1 cylinder  C CylindricalWarperGpu C DisjointSets C DpSeamFinder C Estimator Rotation estimator base class  C ExposureCompensator Base class for all exposure compensators  C FeatherBlender Simple blender which mixes images at its borders  C FeaturesFinder Feature finders base class  C FeaturesMatcher Feature matchers base class  C FisheyeProjector C FisheyeWarper C GainCompensator Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities, see [25] and [211] for details  C Graph C GraphCutSeamFinder Minimum graph cut-based seam estimator. See details in [101] C GraphCutSeamFinderBase Base class for all minimum graph-cut-based seam estimators  C GraphEdge C HomographyBasedEstimator Homography based rotation estimator  C ImageFeatures Structure containing image keypoints and descriptors  C MatchesInfo Structure containing information about matches between two images  C MercatorProjector C MercatorWarper C MultiBandBlender Blender which uses multi-band blending algorithm (see [28] )  C NoBundleAdjuster Stub bundle adjuster that does nothing  C NoExposureCompensator Stub exposure compensator which does nothing  C NoSeamFinder Stub seam estimator which does nothing  C OrbFeaturesFinder ORB features finder. :  C PairwiseSeamFinder Base class for all pairwise seam estimators  C PaniniPortraitProjector C PaniniPortraitWarper C PaniniProjector C PaniniWarper C PlanePortraitProjector C PlanePortraitWarper C PlaneProjector C PlaneWarper Warper that maps an image onto the z = 1 plane  C PlaneWarperGpu C ProjectorBase Base class for warping logic implementation  C RotationWarper Rotation-only model image warper interface  C RotationWarperBase Base class for rotation-based warper using a detail::ProjectorBase_ derived class  C SeamFinder Base class for a seam estimator  C SphericalPortraitProjector C SphericalPortraitWarper C SphericalProjector C SphericalWarper Warper that maps an image onto the unit sphere located at the origin  C SphericalWarperGpu C StereographicProjector C StereographicWarper C SurfFeaturesFinder SURF features finder  C Timelapser C TimelapserCrop C TransverseMercatorProjector C TransverseMercatorWarper C VoronoiSeamFinder Voronoi diagram-based seam estimator  ▼N details C _LayerStaticRegisterer C _Range C AbsLayer C ActivationLayer C BackendNode Derivatives of this class encapsulates functions of certain backends  C BackendWrapper Derivatives of this class wraps cv::Mat for different backends and targets  C BaseConvolutionLayer C BatchNormLayer C BlankLayer C BNLLLayer C ChannelsPReLULayer C ConcatLayer C ConvolutionLayer C CropAndResizeLayer C CropLayer C DeconvolutionLayer C DetectionOutputLayer C Dict This class implements name-value dictionary, values are instances of DictValue C DictValue This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64  C EltwiseLayer C ELULayer C FlattenLayer C InnerProductLayer C InterpLayer Bilinear resize layer from https://github.com/cdmh/deeplab-public C Layer This interface class allows to build new Layers - are building blocks of networks  C LayerFactory Layer factory allows to create instances of registered layers  C LayerParams This class provides all data needed to initialize layer  C LRNLayer C LSTMLayer LSTM recurrent layer  C MaxUnpoolLayer C MVNLayer C Net This class allows to create and manipulate comprehensive artificial neural networks  C NormalizeBBoxLayer Lp - normalization layer  C PaddingLayer Adds extra values for specific axes  C PermuteLayer C PoolingLayer C PowerLayer C PriorBoxLayer C ProposalLayer C RegionLayer C ReLU6Layer C ReLULayer C ReorgLayer C ReshapeLayer C ResizeLayer Resize input 4-dimensional blob by nearest neighbor or bilinear strategy  C RNNLayer Classical recurrent layer  C ScaleLayer C ShiftLayer C ShuffleChannelLayer C SigmoidLayer C SliceLayer C SoftmaxLayer C SplitLayer C TanHLayer C InferBbox A class to post process model predictions  C object Structure to hold the details pertaining to a single bounding box  ▼C DPMDetector This is a C++ abstract class, it provides external user API to work with DPM  C ObjectDetection C BasicFaceRecognizer C BIF C CParams C EigenFaceRecognizer C Facemark Abstract base class for all facemark models  ▼C FacemarkAAM C Config Optional parameter for fitting process  C Data Data container for the facemark::getData function  ▼C Model The model of AAM Algorithm C Texture C Params ▼C FacemarkKazemi C Params ▼C FacemarkLBF C BBox C Params C FacemarkTrain Abstract base class for trainable facemark models  C FaceRecognizer Abstract base class for all face recognition models  C FisherFaceRecognizer C LBPHFaceRecognizer C MACE Minimum Average Correlation Energy Filter useful for authentication with (cancellable) biometrical features. (does not need many positives to train (10-50), and no negatives at all, also robust to noise/salting)  C PredictCollector Abstract base class for all strategies of prediction result handling  ▼C StandardCollector Default predict collector  C PredictResult C AutotunedIndexParams C CompositeIndexParams C CvType C CvType< char > C CvType< double > C CvType< float > C CvType< short > C CvType< unsigned char > C CvType< unsigned short > C GenericIndex The FLANN nearest neighbor index class. This class is templated with the type of elements for which the index is built  C HierarchicalClusteringIndexParams C Index C Index_ C IndexParams C KDTreeIndexParams C KMeansIndexParams C LinearIndexParams C LshIndexParams C SavedIndexParams C SearchParams C FreeType2 C DCT2D C DFT1D C DFT2D C HDF5 Hierarchical Data Format version 5 interface  C HfsSegment C AverageHash Computes average hash value of the input image  C BlockMeanHash Image hash based on block mean  C ColorMomentHash Image hash based on color moments  C ImgHashBase The base class for image hash algorithms  C MarrHildrethHash Marr-Hildreth Operator Based Hash, slowest but more discriminative  C PHash PHash C RadialVarianceHash Image hash based on Radon transform  ▼N instr C NodeData C NodeDataTls ▼N line_descriptor ▼C BinaryDescriptor Class implements both functionalities for detection of lines and computation of their binary descriptor  C Params List of BinaryDescriptor parameters:  C BinaryDescriptorMatcher Furnishes all functionalities for querying a dataset provided by user or internal to class (that user must, anyway, populate) on the model of Descriptor Matchers C DrawLinesMatchesFlags C KeyLine A class to represent a line  C LSDDetector ▼N linemod C ColorGradient Modality that computes quantized gradient orientations from a color image  C DepthNormal Modality that computes quantized surface normals from a dense depth map  C Detector Object detector using the LINE template matching algorithm with any set of modalities  C Feature Discriminant feature described by its location and label  C Match Represents a successful template match  C Modality Interface for modalities that plug into the LINE template matching representation  ▼C QuantizedPyramid Represents a modality operating over an image pyramid  C Candidate Candidate feature with a score  C Template ▼N ml C ANN_MLP Artificial Neural Networks - Multi-Layer Perceptrons  C ANN_MLP_ANNEAL Artificial Neural Networks - Multi-Layer Perceptrons  C Boost Boosted tree classifier derived from DTrees ▼C DTrees The class represents a single decision tree or a collection of decision trees  C Node The class represents a decision tree node  C Split The class represents split in a decision tree The class implements the Expectation Maximization algorithm  C KNearest The class implements K-Nearest Neighbors model  C LogisticRegression Implements Logistic Regression classifier  C NormalBayesClassifier Bayes classifier for normally distributed data  C ParamGrid The structure represents the logarithmic grid range of statmodel parameters  C RTrees The class implements the random forest predictor  C SimulatedAnnealingSolverSystem This class declares example interface for system state used in simulated annealing optimization algorithm  C StatModel Base class for statistical models in OpenCV ML  ▼C SVM Support Vector Machines  C Kernel C SVMSGD Stochastic Gradient Descent SVM classifier  C TrainData Class encapsulating training data  ▼N multicalib ▼C MultiCameraCalibration Class for multiple camera calibration that supports pinhole camera and omnidirection camera. For omnidirectional camera model, please refer to omnidir.hpp in ccalib module. It first calibrate each camera individually, then a bundle adjustment like optimization is applied to refine extrinsic parameters. So far, it only support "random" pattern for calibration, see randomPattern.hpp in ccalib module for details. Images that are used should be named by "cameraIdx-timestamp.*", several images with the same timestamp means that they are the same pattern that are photographed. cameraIdx should start from 0  C edge C vertex ▼N ocl C Context C Device C Image2D C Kernel C KernelArg C Platform C PlatformInfo C Program C ProgramSource C Queue C Timer ▼N ogl C Arrays Wrapper for OpenGL Client-Side Vertex arrays  C Buffer Smart pointer for OpenGL buffer object with reference counting  C Texture2D Smart pointer for OpenGL 2D texture memory with reference counting  ▼N omnidir ▼N optflow C DISOpticalFlow DIS optical flow algorithm  C GPCDetails C GPCForest C GPCMatchingParams Class encapsulating matching parameters  C GPCPatchDescriptor C GPCPatchSample C GPCTrainingParams Class encapsulating training parameters  C GPCTrainingSamples Class encapsulating training samples  ▼C GPCTree Class for individual tree  C Node C OpticalFlowPCAFlow PCAFlow algorithm  C PCAPrior This class can be used for imposing a learned prior on the resulting optical flow. Solution will be regularized according to this prior. You need to generate appropriate prior file with "learn_prior.py" script beforehand  C VariationalRefinement Variational optical flow refinement  ▼N ovis C WindowScene ▼N phase_unwrapping ▼C HistogramPhaseUnwrapping Class implementing two-dimensional phase unwrapping based on [104] This algorithm belongs to the quality-guided phase unwrapping methods. First, it computes a reliability map from second differences between a pixel and its eight neighbours. Reliability values lie between 0 and 16*pi*pi. Then, this reliability map is used to compute the reliabilities of "edges". An edge is an entity defined by two pixels that are connected horizontally or vertically. Its reliability is found by adding the the reliabilities of the two pixels connected through it. Edges are sorted in a histogram based on their reliability values. This histogram is then used to unwrap pixels, starting from the highest quality pixel  C Params Parameters of phaseUnwrapping constructor  C PhaseUnwrapping Abstract base class for phase unwrapping  ▼N plot C Plot2d ▼N ppf_match_3d C ICP This class implements a very efficient and robust variant of the iterative closest point ( ICP ) algorithm. The task is to register a 3D model (or point cloud) against a set of noisy target data. The variants are put together by myself after certain tests. The task is to be able to match partial, noisy point clouds in cluttered scenes, quickly. You will find that my emphasis is on the performance, while retaining the accuracy. This implementation is based on Tolga Birdal's MATLAB implementation in here: http://www.mathworks.com/matlabcentral/fileexchange/47152-icp-registration-using-efficient-variants-and-multi-resolution-scheme The main contributions come from:  C Pose3D Class, allowing the storage of a pose. The data structure stores both the quaternions and the matrix forms. It supports IO functionality together with various helper methods to work with poses  C PoseCluster3D When multiple poses (see Pose3D ) are grouped together (contribute to the same transformation) pose clusters occur. This class is a general container for such groups of poses. It is possible to store, load and perform IO on these poses  C PPF3DDetector Class, allowing the load and matching 3D models. Typical Use:  ▼N randpattern C RandomPatternCornerFinder Class for finding features points and corresponding 3D in world coordinate of a "random" pattern, which can be to be used in calibration. It is useful when pattern is partly occluded or only a part of pattern can be observed in multiple cameras calibration. The pattern can be generated by RandomPatternGenerator class described in this file  C RandomPatternGenerator ▼N reg C Map Base class for modelling a Map between two images  C MapAffine C Mapper Base class for modelling an algorithm for calculating a map  C MapperGradAffine C MapperGradEuclid C MapperGradProj C MapperGradShift C MapperGradSimilar C MapperPyramid C MapProjec C MapShift C MapTypeCaster ▼N rgbd C DepthCleaner C ICPOdometry C Odometry C OdometryFrame C RgbdFrame C RgbdICPOdometry C RgbdNormals C RgbdOdometry C RgbdPlane ▼N saliency C MotionSaliency C MotionSaliencyBinWangApr2014 Fast Self-tuning Background Subtraction Algorithm from [200] C Objectness C ObjectnessBING Objectness algorithms based on [3] [3] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014  C Saliency C StaticSaliency C StaticSaliencyFineGrained Fine Grained Saliency approach from [134] C StaticSaliencySpectralResidual Spectral Residual approach from [85] ▼N sfm C BaseSFM Base class BaseSFM declares a common API that would be used in a typical scene reconstruction scenario  C libmv_CameraIntrinsicsOptions Data structure describing the camera model and its parameters  C libmv_ReconstructionOptions Data structure describing the reconstruction options  C SFMLibmvEuclideanReconstruction SFMLibmvEuclideanReconstruction class provides an interface with the Libmv Structure From Motion pipeline  ▼N stereo C CensusKernel A kernel in which a pixel is compared with the center of the window  C CombinedDescriptor C Matching C MCTKernel C MeanKernelIntegralImage C ModifiedCsCensus C MVKernel C StarKernelCensus Implementation for the star kernel descriptor  C StereoBinaryBM Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige  C StereoBinarySGBM The class implements the modified H. Hirschmuller algorithm [84] that differs from the original one as follows:  C StereoMatcher Filters off small noise blobs (speckles) in the disparity map  C SymetricCensus Paralel implementation of the center symetric census  ▼N structured_light ▼C GrayCodePattern Class implementing the Gray-code pattern, based on [81] C Params Parameters of StructuredLightPattern constructor  ▼C SinusoidalPattern Class implementing Fourier transform profilometry (FTP) , phase-shifting profilometry (PSP) and Fourier-assisted phase-shifting profilometry (FAPS) based on [36] C Params Parameters of SinusoidalPattern constructor  C StructuredLightPattern Abstract base class for generating and decoding structured light patterns  ▼N superres C BroxOpticalFlow C DenseOpticalFlowExt C DualTVL1OpticalFlow C FarnebackOpticalFlow C FrameSource C PyrLKOpticalFlow C SuperResolution Base class for Super Resolution algorithms  ▼N text C BaseOCR ▼C ERFilter Base class for 1st and 2nd stages of Neumann and Matas scene text detection algorithm [138] . :  C Callback Callback with the classifier is made a class  C ERStat The ERStat structure represents a class-specific Extremal Region (ER)  ▼C OCRBeamSearchDecoder OCRBeamSearchDecoder class provides an interface for OCR using Beam Search algorithm  C ClassifierCallback Callback with the character classifier is made a class  ▼C OCRHMMDecoder OCRHMMDecoder class provides an interface for OCR using Hidden Markov Models  C ClassifierCallback Callback with the character classifier is made a class  C OCRHolisticWordRecognizer OCRHolisticWordRecognizer class provides the functionallity of segmented wordspotting. Given a predefined vocabulary , a DictNet is employed to select the most probable word given an input image  C OCRTesseract OCRTesseract class provides an interface with the tesseract-ocr API (v3.02.02) in C++  C TextDetector An abstract class providing interface for text detection algorithms  C TextDetectorCNN TextDetectorCNN class provides the functionallity of text bounding box detection. This class is representing to find bounding boxes of text words given an input image. This class uses OpenCV dnn module to load pre-trained model described in [111] . The original repository with the modified SSD Caffe version: https://github.com/MhLiao/TextBoxes . Model can be downloaded from DropBox . Modified .prototxt file with the model description can be found in opencv_contrib/modules/text/samples/textbox.prototxt ▼N tracking C AugmentedUnscentedKalmanFilterParams Augmented Unscented Kalman filter parameters. The class for initialization parameters of Augmented Unscented Kalman filter  C 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  C UnscentedKalmanFilter The interface for Unscented Kalman filter and Augmented Unscented Kalman filter  C UnscentedKalmanFilterParams Unscented Kalman filter parameters. The class for initialization parameters of Unscented Kalman filter  ▼N utils ▼N logging C lock_guard A simple scoped lock (RAII-style locking for exclusive/write access)  C optional_lock_guard An optional simple scoped lock (RAII-style locking for exclusive/write access)  C optional_shared_lock_guard An optional shared scoped lock (RAII-style locking for shared/reader access)  C shared_lock_guard A shared scoped lock (RAII-style locking for shared/reader access)  ▼N va_intel ▼N videostab C ColorAverageInpainter C ColorInpainter C ConsistentMosaicInpainter C DeblurerBase C FastMarchingMethod Describes the Fast Marching Method implementation  C FromFileMotionReader C GaussianMotionFilter C IDenseOptFlowEstimator C IFrameSource C ILog C ImageMotionEstimatorBase Base class for global 2D motion estimation methods which take frames as input  C IMotionStabilizer C InpainterBase C InpaintingPipeline C IOutlierRejector C ISparseOptFlowEstimator C KeypointBasedMotionEstimator Describes a global 2D motion estimation method which uses keypoints detection and optical flow for matching  C LogToStdout C LpMotionStabilizer C MoreAccurateMotionWobbleSuppressor C MoreAccurateMotionWobbleSuppressorBase C MotionEstimatorBase Base class for all global motion estimation methods  C MotionEstimatorL1 Describes a global 2D motion estimation method which minimizes L1 error  C MotionEstimatorRansacL2 Describes a robust RANSAC-based global 2D motion estimation method which minimizes L2 error  C MotionFilterBase C MotionInpainter C MotionStabilizationPipeline C NullDeblurer C NullFrameSource C NullInpainter C NullLog C NullOutlierRejector C NullWobbleSuppressor C OnePassStabilizer C PyrLkOptFlowEstimatorBase C RansacParams Describes RANSAC method parameters  C SparsePyrLkOptFlowEstimator C StabilizerBase C ToFileMotionWriter C TranslationBasedLocalOutlierRejector C TwoPassStabilizer C VideoFileSource C WeightingDeblurer C WobbleSuppressorBase ▼N viz C Camera This class wraps intrinsic parameters of a camera  C Color This class represents color in BGR order  C KeyboardEvent This class represents a keyboard event  C Mesh This class wraps mesh attributes, and it can load a mesh from a ply file. :  C MouseEvent This class represents a mouse event  C Viz3d 3D visualizer window. This class is implicitly shared  C WArrow This 3D Widget defines an arrow  C WCameraPosition This 3D Widget represents camera position in a scene by its axes or viewing frustum. :  C WCircle This 3D Widget defines a circle  C WCloud Clouds  C WCloudCollection This 3D Widget defines a collection of clouds. :  C WCloudNormals This 3D Widget represents normals of a point cloud. :  C WCone This 3D Widget defines a cone. :  C WCoordinateSystem Compound widgets  C WCube This 3D Widget defines a cube  C WCylinder This 3D Widget defines a cylinder. :  C WGrid This 3D Widget defines a grid. :  C Widget Base class of all widgets. Widget is implicitly shared  C Widget2D Base class of all 2D widgets  C Widget3D Base class of all 3D widgets  C WidgetAccessor This class is for users who want to develop their own widgets using VTK library API. :  C WImage3D This 3D Widget represents an image in 3D space. :  C WImageOverlay This 2D Widget represents an image overlay. :  C WLine Simple widgets  C WMesh Constructs a WMesh C WPaintedCloud C WPlane This 3D Widget defines a finite plane  C WPolyLine This 3D Widget defines a poly line. :  C WSphere This 3D Widget defines a sphere. :  C WText Text and image widgets  C WText3D This 3D Widget represents 3D text. The text always faces the camera  C WTrajectory Trajectories  C WTrajectoryFrustums This 3D Widget represents a trajectory. :  C WTrajectorySpheres This 3D Widget represents a trajectory using spheres and lines  C WWidgetMerger This class allows to merge several widgets to single one  ▼N xfeatures2d C AffineFeature2D Class implementing affine adaptation for key points  C BoostDesc Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in [176] and [177] C BriefDescriptorExtractor Class for computing BRIEF descriptors described in [29] C DAISY Class implementing DAISY descriptor, described in [183] C Elliptic_KeyPoint Elliptic region around an interest point  C FREAK Class implementing the FREAK ( Fast Retina Keypoint ) keypoint descriptor, described in [4] C HarrisLaplaceFeatureDetector Class implementing the Harris-Laplace feature detector as described in [131] C LATCH C LUCID Class implementing the locally uniform comparison image descriptor, described in [222] C MSDDetector Class implementing the MSD ( Maximal Self-Dissimilarity ) keypoint detector, described in [184] C PCTSignatures Class implementing PCT (position-color-texture) signature extraction as described in [100] . The algorithm is divided to a feature sampler and a clusterizer. Feature sampler produces samples at given set of coordinates. Clusterizer then produces clusters of these samples using k-means algorithm. Resulting set of clusters is the signature of the input image  C PCTSignaturesSQFD Class implementing Signature Quadratic Form Distance (SQFD)  C SIFT Class for extracting keypoints and computing descriptors using the Scale Invariant Feature Transform ( SIFT ) algorithm by D. Lowe [118] C StarDetector The class implements the keypoint detector introduced by [2] , synonym of StarDetector . :  C SURF Class for extracting Speeded Up Robust Features from an image [10] C VGG Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [168] ▼N ximgproc ▼N segmentation C GraphSegmentation Graph Based Segmentation Algorithm . The class implements the algorithm described in [54] C SelectiveSearchSegmentation Selective search segmentation algorithm The class implements the algorithm described in [188] C SelectiveSearchSegmentationStrategy Strategie for the selective search segmentation algorithm The class implements a generic stragery for the algorithm described in [188] C SelectiveSearchSegmentationStrategyColor Color-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [188] C SelectiveSearchSegmentationStrategyFill Fill-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [188] C SelectiveSearchSegmentationStrategyMultiple Regroup multiple strategies for the selective search segmentation algorithm  C SelectiveSearchSegmentationStrategySize Size-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [188] C SelectiveSearchSegmentationStrategyTexture Texture-based strategy for the selective search segmentation algorithm The class is implemented from the algorithm described in [188] C AdaptiveManifoldFilter Interface for Adaptive Manifold Filter realizations  C Box C ContourFitting Class for ContourFitting algorithms. ContourFitting match two contours zaand zb minimizing distance

d(za,zb)=∑(an−sbnej(nα+ϕ))2

where an and bn are Fourier descriptors of za and zb and s is a scaling factor and ϕ is angle rotation and α is starting point factor adjustement

C DisparityFilter Main interface for all disparity map filters  C 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  C DTFilter Interface for realizations of Domain Transform filter  C EdgeAwareInterpolator Sparse match interpolation algorithm based on modified locally-weighted affine estimator from [155] and Fast Global Smoother as post-processing filter  C EdgeBoxes Class implementing EdgeBoxes algorithm from [224] :  C FastGlobalSmootherFilter Interface for implementations of Fast Global Smoother filter  C FastLineDetector Class implementing the FLD (Fast Line Detector ) algorithm described in [103] C GuidedFilter Interface for realizations of Guided Filter  C RFFeatureGetter C RidgeDetectionFilter Applies Ridge Detection Filter to an input image. Implements Ridge detection similar to the one in Mathematica using the eigen values from the Hessian Matrix of the input image using Sobel Derivatives. Additional refinement can be done using Skeletonization and Binarization  C 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  C StructuredEdgeDetection Class implementing edge detection algorithm from [43] :  C SuperpixelLSC Class implementing the LSC (Linear Spectral Clustering) superpixels algorithm described in [107] C SuperpixelSEEDS Class implementing the SEEDS (Superpixels Extracted via Energy-Driven Sampling) superpixels algorithm described in [192] C SuperpixelSLIC Class implementing the SLIC (Simple Linear Iterative Clustering) superpixels algorithm described in [1] ▼N xobjdetect C WBDetector WaldBoost detector  ▼N xphoto C GrayworldWB Gray-world white balance algorithm  C LearningBasedWB More sophisticated learning-based automatic white balance algorithm  C SimpleWB A simple white balance algorithm that works by independently stretching each of the input image channels to the specified range. For increased robustness it ignores the top and bottom p% of pixel values  C WhiteBalancer The base class for auto white balance algorithms  C _InputArray This is the proxy class for passing read-only input arrays into OpenCV functions  C _InputOutputArray C _OutputArray This type is very similar to InputArray except that it is used for input/output and output function parameters  C Accumulator C Accumulator< char > C Accumulator< short > C Accumulator< unsigned char > C Accumulator< unsigned short > C Affine3 Affine transform  C AffineTransformer Wrapper class for the OpenCV Affine Transformation algorithm. :  C AffineWarper Affine warper factory class  C AgastFeatureDetector Wrapping class for feature detection using the AGAST method. :  C AKAZE Class implementing the AKAZE keypoint detector and descriptor extractor, described in [5] C Algorithm This is a base class for all more or less complex algorithms in OpenCV  C AlignExposures The base class for algorithms that align images of the same scene with different exposures  C 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  ▼C Allocator C rebind C AutoBuffer Automatically Allocated Buffer Class  C AutoLock C AVIReadContainer C AVIWriteContainer C BackgroundSubtractor Base class for background/foreground segmentation. :  C BackgroundSubtractorKNN K-nearest neighbours - based Background/Foreground Segmentation Algorithm C BackgroundSubtractorMOG2 Gaussian Mixture-based Background/Foreground Segmentation Algorithm ▼C BaseCascadeClassifier C MaskGenerator C BaseClassifier C BFMatcher Brute-force descriptor matcher  C BOWImgDescriptorExtractor Class to compute an image descriptor using the bag of visual words C BOWKMeansTrainer Kmeans -based class to train visual vocabulary using the bag of visual words approach. :  C BOWTrainer Abstract base class for training the bag of visual words vocabulary from a set of descriptors  C BRISK Class implementing the BRISK keypoint detector and descriptor extractor, described in [106] C BufferPoolController C CalibrateCRF The base class for camera response calibration algorithms  C CalibrateDebevec Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. Objective function is constructed using pixel values on the same position in all images, extra term is added to make the result smoother  C CalibrateRobertson Inverse camera response function is extracted for each brightness value by minimizing an objective function as linear system. This algorithm uses all image pixels  C CascadeClassifier Cascade classifier class for object detection  C ChiHistogramCostExtractor An Chi based cost extraction. :  C CirclesGridFinderParameters C CirclesGridFinderParameters2 C CLAHE Base class for Contrast Limited Adaptive Histogram Equalization. :  C ClassifierThreshold ▼C ClfMilBoost C Params C ClfOnlineStump C CommandLineParser Designed for command line parsing  C Complex A complex number class  C CompressedRectilinearPortraitWarper C CompressedRectilinearWarper C ConjGradSolver This class is used to perform the non-linear non-constrained minimization of a function with known gradient,  C CvFeatureEvaluator C CvFeatureParams ▼C CvHaarEvaluator C FeatureHaar C CvHaarFeatureParams ▼C CvHOGEvaluator C Feature C CvHOGFeatureParams ▼C CvLBPEvaluator C Feature C CvLBPFeatureParams C CvParams C CylindricalWarper Cylindrical warper factory class  C DataDepth A helper class for cv::DataType C DataType Template "trait" class for OpenCV primitive data types  C DenseOpticalFlow ▼C DescriptorMatcher Abstract base class for matching keypoint descriptors  C DescriptorCollection C DetectionROI Struct for detection region of interest (ROI)  C Detector C DMatch Class for matching keypoint descriptors  C DownhillSolver This class is used to perform the non-linear non-constrained minimization of a function,  C DrawMatchesFlags C DualTVL1OpticalFlow "Dual TV L1" Optical Flow Algorithm C EMDHistogramCostExtractor An EMD based cost extraction. :  C EMDL1HistogramCostExtractor An EMD-L1 based cost extraction. :  C EstimatedGaussDistribution C Exception Class passed to an error  C FarnebackOpticalFlow Class computing a dense optical flow using the Gunnar Farneback's algorithm  C FastFeatureDetector Wrapping class for feature detection using the FAST method. :  C Feature2D Abstract base class for 2D image feature detectors and descriptor extractors  C FileNode File Storage Node class  ▼C FileNodeIterator Used to iterate through sequences and mappings  C SeqReader C FileStorage XML/YAML/JSON file storage class that encapsulates all the information necessary for writing or reading data to/from a file  C FisheyeWarper C FlannBasedMatcher Flann-based descriptor matcher  C Formatted C Formatter C GeneralizedHough Finds arbitrary template in the grayscale image using Generalized Hough Transform  C GeneralizedHoughBallard C GeneralizedHoughGuil C GFTTDetector Wrapping class for feature detection using the goodFeaturesToTrack function. :  C Hamming C HausdorffDistanceExtractor A simple Hausdorff distance measure between shapes defined by contours  C HistogramCostExtractor Abstract base class for histogram cost algorithms  C HOGDescriptor Implementation of HOG (Histogram of Oriented Gradients) descriptor and object detector  C KalmanFilter Kalman filter class  C KAZE Class implementing the KAZE keypoint detector and descriptor extractor, described in [6] C KeyPoint Data structure for salient point detectors  C KeyPointsFilter A class filters a vector of keypoints  C LDA Linear Discriminant Analysis  C LineIterator Line iterator  C LineSegmentDetector Line segment detector class  C Mat N-dimensional dense array class  C Mat_ Template matrix class derived from Mat C MatAllocator Custom array allocator  C MatCommaInitializer_ Comma-separated Matrix Initializer  C MatConstIterator C MatConstIterator_ Matrix read-only iterator  C MatExpr Matrix expression representation  C MatIterator_ Matrix read-write iterator  C MatOp C MatSize C MatStep C Matx Template class for small matrices whose type and size are known at compilation time  C MatxCommaInitializer Comma-separated Matrix Initializer  C MercatorWarper C MergeDebevec The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response  C MergeExposures The base class algorithms that can merge exposure sequence to a single image  C MergeMertens Pixels are weighted using contrast, saturation and well-exposedness measures, than images are combined using laplacian pyramids  C MergeRobertson The resulting HDR image is calculated as weighted average of the exposures considering exposure values and camera response  ▼C MinProblemSolver Basic interface for all solvers  C Function Represents function being optimized  C Moments Struct returned by cv::moments C MSER Maximally stable extremal region extractor  C MultiTracker This class is used to track multiple objects using the specified tracker algorithm. The MultiTracker is naive implementation of multiple object tracking. It process the tracked objects independently without any optimization accross the tracked objects  C MultiTracker_Alt Base abstract class for the long-term Multi Object Trackers:  C MultiTrackerTLD Multi Object Tracker for TLD. TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into tracking, learning and detection  C Mutex C NAryMatIterator N-ary multi-dimensional array iterator  C Node C NormHistogramCostExtractor A norm based cost extraction. :  C ORB Class implementing the ORB ( oriented BRIEF ) keypoint detector and descriptor extractor  C PaniniPortraitWarper C PaniniWarper C ParallelLoopBody Base class for parallel data processors  C Param C ParamType C ParamType< Algorithm > C ParamType< bool > C ParamType< double > C ParamType< float > C ParamType< Mat > C ParamType< Scalar > C ParamType< std::vector< Mat > > C ParamType< String > C ParamType< uchar > C ParamType< uint64 > C ParamType< unsigned > C PCA Principal Component Analysis  C PlaneWarper Plane warper factory class  C Point3_ Template class for 3D points specified by its coordinates x , y and z C Point_ Template class for 2D points specified by its coordinates x and y C Ptr Template class for smart pointers with shared ownership  C QtFont QtFont available only for Qt. See cv::fontQt C Range Template class specifying a continuous subsequence (slice) of a sequence  C Rect_ Template class for 2D rectangles  C RNG Random Number Generator  C RNG_MT19937 Mersenne Twister random number generator  C RotatedRect The class represents rotated (i.e. not up-right) rectangles on a plane  C Scalar_ Template class for a 4-element vector derived from Vec C Seq C SeqIterator C ShapeContextDistanceExtractor Implementation of the Shape Context descriptor and matching algorithm  C ShapeDistanceExtractor Abstract base class for shape distance algorithms  C ShapeTransformer Abstract base class for shape transformation algorithms  C SimilarRects ▼C SimpleBlobDetector Class for extracting blobs from an image. :  C Params C Size_ Template class for specifying the size of an image or rectangle  C SL2 C softdouble C softfloat ▼C SparseMat The class SparseMat represents multi-dimensional sparse numerical arrays  C Hdr Sparse matrix header  C Node Sparse matrix node - element of a hash table  C SparseMat_ Template sparse n-dimensional array class derived from SparseMat C SparseMatConstIterator Read-Only Sparse Matrix Iterator  C SparseMatConstIterator_ Template Read-Only Sparse Matrix Iterator Class  C SparseMatIterator Read-write Sparse Matrix Iterator  C SparseMatIterator_ Template Read-Write Sparse Matrix Iterator Class  C SparseOpticalFlow Base interface for sparse optical flow algorithms  C SparsePyrLKOpticalFlow Class used for calculating a sparse optical flow  C SphericalWarper Spherical warper factory class  C StereoBM Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige  C StereographicWarper C StereoMatcher The base class for stereo correspondence algorithms  C StereoSGBM The class implements the modified H. Hirschmuller algorithm [84] that differs from the original one as follows:  C Stitcher High level image stitcher  C String C StrongClassifierDirectSelection ▼C Subdiv2D C QuadEdge C Vertex C SVD Singular Value Decomposition  C TermCriteria The class defining termination criteria for iterative algorithms  C ThinPlateSplineShapeTransformer Definition of the transformation  C TickMeter Class to measure passing time  C TLSData C TLSDataContainer C Tonemap Base class for tonemapping algorithms - tools that are used to map HDR image to 8-bit range  C TonemapDrago Adaptive logarithmic mapping is a fast global tonemapping algorithm that scales the image in logarithmic domain  C 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  C 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. After this the image is reconstructed from new contrast values  C TonemapReinhard This is a global tonemapping operator that models human visual system  C Tracker Base abstract class for the long-term tracker:  ▼C TrackerBoosting This is a real-time object tracking based on a novel on-line version of the AdaBoost algorithm  C Params ▼C TrackerCSRT Discriminative Correlation Filter Tracker with Channel and Spatial Reliability  C Params C TrackerFeature Abstract base class for TrackerFeature that represents the feature  C TrackerFeatureFeature2d TrackerFeature based on Feature2D ▼C TrackerFeatureHAAR TrackerFeature based on HAAR features, used by TrackerMIL and many others algorithms  C Params C TrackerFeatureHOG TrackerFeature based on HOG  C TrackerFeatureLBP TrackerFeature based on LBP  C TrackerFeatureSet Class that manages the extraction and selection of features  ▼C TrackerGOTURN GOTURN ( [79] ) is kind of trackers based on Convolutional Neural Networks (CNN). While taking all advantages of CNN trackers, GOTURN is much faster due to offline training without online fine-tuning nature. GOTURN tracker addresses the problem of single target tracking: given a bounding box label of an object in the first frame of the video, we track that object through the rest of the video. NOTE: Current method of GOTURN does not handle occlusions; however, it is fairly robust to viewpoint changes, lighting changes, and deformations. Inputs of GOTURN are two RGB patches representing Target and Search patches resized to 227x227. Outputs of GOTURN are predicted bounding box coordinates, relative to Search patch coordinate system, in format X1,Y1,X2,Y2. Original paper is here: http://davheld.github.io/GOTURN/GOTURN.pdf As long as original authors implementation: https://github.com/davheld/GOTURN#train-the-tracker Implementation of training algorithm is placed in separately here due to 3d-party dependencies: https://github.com/Auron-X/GOTURN_Training_Toolkit GOTURN architecture goturn.prototxt and trained model goturn.caffemodel are accessible on opencv_extra GitHub repository  C Params ▼C TrackerKCF KCF is a novel tracking framework that utilizes properties of circulant matrix to enhance the processing speed. This tracking method is an implementation of [80] which is extended to KCF with color-names features ( [38] ). The original paper of KCF is available at http://www.robots.ox.ac.uk/~joao/publications/henriques_tpami2015.pdf as well as the matlab implementation. For more information about KCF with color-names features, please refer to http://www.cvl.isy.liu.se/research/objrec/visualtracking/colvistrack/index.html C Params ▼C TrackerMedianFlow Median Flow tracker implementation  C Params ▼C TrackerMIL The MIL algorithm trains a classifier in an online manner to separate the object from the background  C Params C TrackerModel Abstract class that represents the model of the target. It must be instantiated by specialized tracker  C TrackerMOSSE MOSSE tracker note, that this tracker works with grayscale images, if passed bgr ones, they will get converted internally. [17] Visual Object Tracking using Adaptive Correlation Filters  C 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  C TrackerSamplerAlgorithm Abstract base class for TrackerSamplerAlgorithm that represents the algorithm for the specific sampler  ▼C TrackerSamplerCS TrackerSampler based on CS (current state), used by algorithm TrackerBoosting C Params ▼C TrackerSamplerCSC TrackerSampler based on CSC (current state centered), used by MIL algorithm TrackerMIL C Params ▼C TrackerSamplerPF This sampler is based on particle filtering  C Params This structure contains all the parameters that can be varied during the course of sampling algorithm. Below is the structure exposed, together with its members briefly explained with reference to the above discussion on algorithm's working  C TrackerStateEstimator Abstract base class for TrackerStateEstimator that estimates the most likely target state  ▼C TrackerStateEstimatorAdaBoosting TrackerStateEstimatorAdaBoosting based on ADA-Boosting  C TrackerAdaBoostingTargetState Implementation of the target state for TrackerAdaBoostingTargetState ▼C TrackerStateEstimatorMILBoosting TrackerStateEstimator based on Boosting  C TrackerMILTargetState C TrackerStateEstimatorSVM TrackerStateEstimator based on SVM  C TrackerTargetState Abstract base class for TrackerTargetState that represents a possible state of the target  ▼C TrackerTLD TLD is a novel tracking framework that explicitly decomposes the long-term tracking task into tracking, learning and detection  C Params C TransverseMercatorWarper C UMat C UMatData C v_reg C Vec Template class for short numerical vectors, a partial case of Matx C VecCommaInitializer Comma-separated Vec Initializer  C VideoCapture Class for video capturing from video files, image sequences or cameras  C VideoWriter Video writer class  C WarperCreator Image warper factories base class  C WeakClassifierHaarFeature C WImage Image class which provides a thin layer around an IplImage C WImageBuffer C WImageBufferC C WImageC C WImageView C WImageViewC ▼N cvflann ▼N anyimpl C bad_any_cast C base_any_policy C choose_policy C choose_policy< any > C choose_policy< bool > C choose_policy< float > C choose_policy< signed char > C choose_policy< signed long > C choose_policy< signed short > C choose_policy< T * > C choose_policy< unsigned char > C choose_policy< unsigned long > C choose_policy< unsigned short > C CV_FINAL C empty_any C SinglePolicy C typed_base_any_policy ▼N lsh C LshStats C LshTable C Accumulator C Accumulator< char > C Accumulator< short > C Accumulator< unsigned char > C Accumulator< unsigned short > C any C AutotunedIndex C AutotunedIndexParams C BranchStruct C ChiSquareDistance C CompositeIndex C CompositeIndexParams C CreatorNotFound C Datatype C Datatype< char > C Datatype< double > C Datatype< float > C Datatype< short > C Datatype< unsigned char > C Datatype< unsigned short > C DynamicBitset C False C FLANNException C Hamming C Hamming2 C HammingLUT ▼C Heap C CompareT C HellingerDistance C HierarchicalClusteringIndex C HierarchicalClusteringIndexParams C HistIntersectionDistance C Index C index_creator C index_creator< False, False, Distance > C index_creator< False, VectorSpace, Distance > C IndexHeader C KDTreeIndex C KDTreeIndexParams C KDTreeSingleIndex C KDTreeSingleIndexParams C KL_Divergence ▼C KMeansIndex C KMeansDistanceComputer C KMeansIndexParams C KNNRadiusUniqueResultSet C KNNResultSet C KNNSimpleResultSet C KNNUniqueResultSet C L2_Simple C LinearIndex C LinearIndexParams C Logger C LshIndex C LshIndexParams C Matrix C MaxDistance C MinkowskiDistance C NNIndex C ObjectFactory C PooledAllocator C RadiusResultSet C RadiusUniqueResultSet C ResultSet C SavedIndexParams C SearchParams C simpleDistance C simpleDistance< ChiSquareDistance< ElementType >, ElementType > C simpleDistance< HellingerDistance< ElementType >, ElementType > C simpleDistance< L2< ElementType >, ElementType > C simpleDistance< L2_Simple< ElementType >, ElementType > C simpleDistance< MinkowskiDistance< ElementType >, ElementType > C squareDistance C squareDistance< ChiSquareDistance< ElementType >, ElementType > C squareDistance< HellingerDistance< ElementType >, ElementType > C squareDistance< L2< ElementType >, ElementType > C squareDistance< L2_Simple< ElementType >, ElementType > C squareDistance< MinkowskiDistance< ElementType >, ElementType > C StartStopTimer C True C UniqueRandom ▼C UniqueResultSet C DistIndex C UntypedMatrix C ZeroIterator ▼N cvv ▼N impl C CallMetaData Optional information about a location in Code  C FinalShowCaller RAII-class to call finalShow() in it's dtor  ▼N matlab C ArgumentParser Parses inputs to a method and resolves the argument names  C DefaultTraits C InheritType C Map C MxArray A thin wrapper around Matlab's mxArray types  C Traits C Traits< bool > C Traits< char > C Traits< double > C Traits< float > C Traits< int16_t > C Traits< int32_t > C Traits< int64_t > C Traits< int8_t > C Traits< matlab::InheritType > C Traits< uint16_t > C Traits< uint32_t > C Traits< uint64_t > C Traits< uint8_t > ▼N NcvCTprep C assertTest C CT_ASSERT_FAILURE C CT_ASSERT_FAILURE< true > C <AVCaptureVideoDataOutputSampleBufferDelegate> ▼C Cv16suf C _fp16Format ▼C Cv32suf C _fp32Format C Cv64suf C CvAbstractCamera C CvAttrList List of attributes. :  C CvAvgComp C CvBox2D C CvChain C CvChainPtReader C CvConnectedComp C CvContour C CvConvexityDefect C CvFileNode C CvFont C CvGraph C CvGraphEdge C CvGraphScanner C CvGraphVtx C CvGraphVtx2D C CvHaarClassifier C CvHaarClassifierCascade C CvHaarFeature C CvHaarStageClassifier C cvhalDFT Dummy structure storing DFT/DCT context  C cvhalFilter2D Dummy structure storing filtering context  C cvhalKeyPoint C CvHistogram C CvHuMoments C CvKalman C CvLevMarq C CvLineIterator C CvMat C CvMatND C CvMemBlock C CvMemStorage C CvMemStoragePos C CvModuleInfo C CvMoments C CvNArrayIterator C CvPhotoCamera C <CvPhotoCameraDelegate > C CvPluginFuncInfo C CvPoint C CvPoint2D32f C CvPoint2D64f C CvPoint3D32f C CvPoint3D64f C CvRect C CvScalar C CvSeq C CvSeqBlock C CvSeqReader C CvSeqWriter C CvSet C CvSetElem C CvSize C CvSize2D32f C CvSlice C CvSparseMat C CvSparseMatIterator C CvSparseNode C CvStereoBMState C CvString C CvStringHashNode C CvTermCriteria C CvTreeNodeIterator C CvType Class for automatic module/RTTI data registration/unregistration  C CvTypeInfo Type information  C CvVideoCamera C <CvVideoCameraDelegate > C Gray2RGB C HaarClassifierCascadeDescriptor C HaarClassifierNode128 C HaarClassifierNodeDescriptor32 C HaarFeature64 C HaarFeatureDescriptor32 C HaarStage64 C hashnode_i C hashtable_int C HLS2RGB C HSV2RGB C INCVMemAllocator C IplConvKernel C IplConvKernelFP C IplImage C IplROI C Lab2RGB C Luv2RGB C NCVBroxOpticalFlowDescriptor Model and solver parameters  C NCVMatrix C NCVMatrixAlloc C NCVMatrixReuse C NCVMemNativeAllocator C NCVMemPtr C NCVMemSegment C NCVMemStackAllocator C NcvPoint2D32s C NcvPoint2D32u C NcvRect32s C NcvRect32u C NcvRect8u C NcvSize32s C NcvSize32u C NCVVector C NCVVectorAlloc C NCVVectorReuse C NppStInterpolationState C NSObject C <NSObject> C <NSObjectNSObject> C RGB2Gray C RGB2HLS C RGB2HSV C RGB2Lab C RGB2Luv C RGB2RGB C RGB2XYZ C RGB2YCrCb C RGB2YUV C THash Struct, holding a node in the hashtable  C XYZ2RGB C YCrCb2RGB C YUV2RGB