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+/*
+By downloading, copying, installing or using the software you agree to this
+license. If you do not agree to this license, do not download, install,
+copy or use the software.
+
+                          License Agreement
+               For Open Source Computer Vision Library
+                       (3-clause BSD License)
+
+Copyright (C) 2013, OpenCV Foundation, all rights reserved.
+Third party copyrights are property of their respective owners.
+
+Redistribution and use in source and binary forms, with or without modification,
+are permitted provided that the following conditions are met:
+
+  * Redistributions of source code must retain the above copyright notice,
+    this list of conditions and the following disclaimer.
+
+  * Redistributions in binary form must reproduce the above copyright notice,
+    this list of conditions and the following disclaimer in the documentation
+    and/or other materials provided with the distribution.
+
+  * Neither the names of the copyright holders nor the names of the contributors
+    may be used to endorse or promote products derived from this software
+    without specific prior written permission.
+
+This software is provided by the copyright holders and contributors "as is" and
+any express or implied warranties, including, but not limited to, the implied
+warranties of merchantability and fitness for a particular purpose are
+disclaimed. In no event shall copyright holders or contributors be liable for
+any direct, indirect, incidental, special, exemplary, or consequential damages
+(including, but not limited to, procurement of substitute goods or services;
+loss of use, data, or profits; or business interruption) however caused
+and on any theory of liability, whether in contract, strict liability,
+or tort (including negligence or otherwise) arising in any way out of
+the use of this software, even if advised of the possibility of such damage.
+*/
+
+#ifndef __OPENCV_ARUCO_HPP__
+#define __OPENCV_ARUCO_HPP__
+
+#include <opencv2/core.hpp>
+#include <vector>
+#include "opencv2/aruco/dictionary.hpp"
+
+/**
+ * @defgroup aruco ArUco Marker Detection
+ * This module is dedicated to square fiducial markers (also known as Augmented Reality Markers)
+ * These markers are useful for easy, fast and robust camera pose estimation.ç
+ *
+ * The main functionalities are:
+ * - Detection of markers in a image
+ * - Pose estimation from a single marker or from a board/set of markers
+ * - Detection of ChArUco board for high subpixel accuracy
+ * - Camera calibration from both, ArUco boards and ChArUco boards.
+ * - Detection of ChArUco diamond markers
+ * The samples directory includes easy examples of how to use the module.
+ *
+ * The implementation is based on the ArUco Library by R. Muñoz-Salinas and S. Garrido-Jurado.
+ *
+ * @sa S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and M. J. Marín-Jiménez. 2014.
+ * "Automatic generation and detection of highly reliable fiducial markers under occlusion".
+ * Pattern Recogn. 47, 6 (June 2014), 2280-2292. DOI=10.1016/j.patcog.2014.01.005
+ *
+ * @sa http://www.uco.es/investiga/grupos/ava/node/26
+ *
+ * This module has been originally developed by Sergio Garrido-Jurado as a project
+ * for Google Summer of Code 2015 (GSoC 15).
+ *
+ *
+*/
+
+namespace cv {
+namespace aruco {
+
+//! @addtogroup aruco
+//! @{
+
+
+
+/**
+ * @brief Parameters for the detectMarker process:
+ * - adaptiveThreshWinSizeMin: minimum window size for adaptive thresholding before finding
+ *   contours (default 3).
+ * - adaptiveThreshWinSizeMax: maximum window size for adaptive thresholding before finding
+ *   contours (default 23).
+ * - adaptiveThreshWinSizeStep: increments from adaptiveThreshWinSizeMin to adaptiveThreshWinSizeMax
+ *   during the thresholding (default 10).
+ * - adaptiveThreshConstant: constant for adaptive thresholding before finding contours (default 7)
+ * - minMarkerPerimeterRate: determine minimum perimeter for marker contour to be detected. This
+ *   is defined as a rate respect to the maximum dimension of the input image (default 0.03).
+ * - maxMarkerPerimeterRate:  determine maximum perimeter for marker contour to be detected. This
+ *   is defined as a rate respect to the maximum dimension of the input image (default 4.0).
+ * - polygonalApproxAccuracyRate: minimum accuracy during the polygonal approximation process to
+ *   determine which contours are squares.
+ * - minCornerDistanceRate: minimum distance between corners for detected markers relative to its
+ *   perimeter (default 0.05)
+ * - minDistanceToBorder: minimum distance of any corner to the image border for detected markers
+ *   (in pixels) (default 3)
+ * - minMarkerDistanceRate: minimum mean distance beetween two marker corners to be considered
+ *   similar, so that the smaller one is removed. The rate is relative to the smaller perimeter
+ *   of the two markers (default 0.05).
+ * - doCornerRefinement: do subpixel refinement or not
+ * - cornerRefinementWinSize: window size for the corner refinement process (in pixels) (default 5).
+ * - cornerRefinementMaxIterations: maximum number of iterations for stop criteria of the corner
+ *   refinement process (default 30).
+ * - cornerRefinementMinAccuracy: minimum error for the stop cristeria of the corner refinement
+ *   process (default: 0.1)
+ * - markerBorderBits: number of bits of the marker border, i.e. marker border width (default 1).
+ * - perpectiveRemovePixelPerCell: number of bits (per dimension) for each cell of the marker
+ *   when removing the perspective (default 8).
+ * - perspectiveRemoveIgnoredMarginPerCell: width of the margin of pixels on each cell not
+ *   considered for the determination of the cell bit. Represents the rate respect to the total
+ *   size of the cell, i.e. perpectiveRemovePixelPerCell (default 0.13)
+ * - maxErroneousBitsInBorderRate: maximum number of accepted erroneous bits in the border (i.e.
+ *   number of allowed white bits in the border). Represented as a rate respect to the total
+ *   number of bits per marker (default 0.35).
+ * - minOtsuStdDev: minimun standard deviation in pixels values during the decodification step to
+ *   apply Otsu thresholding (otherwise, all the bits are set to 0 or 1 depending on mean higher
+ *   than 128 or not) (default 5.0)
+ * - errorCorrectionRate error correction rate respect to the maximun error correction capability
+ *   for each dictionary. (default 0.6).
+ */
+struct CV_EXPORTS_W DetectorParameters {
+
+    DetectorParameters();
+
+    CV_WRAP static Ptr<DetectorParameters> create();
+
+    CV_PROP_RW int adaptiveThreshWinSizeMin;
+    CV_PROP_RW int adaptiveThreshWinSizeMax;
+    CV_PROP_RW int adaptiveThreshWinSizeStep;
+    CV_PROP_RW double adaptiveThreshConstant;
+    CV_PROP_RW double minMarkerPerimeterRate;
+    CV_PROP_RW double maxMarkerPerimeterRate;
+    CV_PROP_RW double polygonalApproxAccuracyRate;
+    CV_PROP_RW double minCornerDistanceRate;
+    CV_PROP_RW int minDistanceToBorder;
+    CV_PROP_RW double minMarkerDistanceRate;
+    CV_PROP_RW bool doCornerRefinement;
+    CV_PROP_RW int cornerRefinementWinSize;
+    CV_PROP_RW int cornerRefinementMaxIterations;
+    CV_PROP_RW double cornerRefinementMinAccuracy;
+    CV_PROP_RW int markerBorderBits;
+    CV_PROP_RW int perspectiveRemovePixelPerCell;
+    CV_PROP_RW double perspectiveRemoveIgnoredMarginPerCell;
+    CV_PROP_RW double maxErroneousBitsInBorderRate;
+    CV_PROP_RW double minOtsuStdDev;
+    CV_PROP_RW double errorCorrectionRate;
+};
+
+
+
+/**
+ * @brief Basic marker detection
+ *
+ * @param image input image
+ * @param dictionary indicates the type of markers that will be searched
+ * @param corners vector of detected marker corners. For each marker, its four corners
+ * are provided, (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers,
+ * the dimensions of this array is Nx4. The order of the corners is clockwise.
+ * @param ids vector of identifiers of the detected markers. The identifier is of type int
+ * (e.g. std::vector<int>). For N detected markers, the size of ids is also N.
+ * The identifiers have the same order than the markers in the imgPoints array.
+ * @param parameters marker detection parameters
+ * @param rejectedImgPoints contains the imgPoints of those squares whose inner code has not a
+ * correct codification. Useful for debugging purposes.
+ *
+ * Performs marker detection in the input image. Only markers included in the specific dictionary
+ * are searched. For each detected marker, it returns the 2D position of its corner in the image
+ * and its corresponding identifier.
+ * Note that this function does not perform pose estimation.
+ * @sa estimatePoseSingleMarkers,  estimatePoseBoard
+ *
+ */
+CV_EXPORTS_W void detectMarkers(InputArray image, const Ptr<Dictionary> &dictionary, OutputArrayOfArrays corners,
+                                OutputArray ids, const Ptr<DetectorParameters> &parameters = DetectorParameters::create(),
+                                OutputArrayOfArrays rejectedImgPoints = noArray());
+
+
+
+/**
+ * @brief Pose estimation for single markers
+ *
+ * @param corners vector of already detected markers corners. For each marker, its four corners
+ * are provided, (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers,
+ * the dimensions of this array should be Nx4. The order of the corners should be clockwise.
+ * @sa detectMarkers
+ * @param markerLength the length of the markers' side. The returning translation vectors will
+ * be in the same unit. Normally, unit is meters.
+ * @param cameraMatrix input 3x3 floating-point camera matrix
+ * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$
+ * @param distCoeffs vector of distortion coefficients
+ * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
+ * @param rvecs array of output rotation vectors (@sa Rodrigues) (e.g. std::vector<cv::Vec3d>).
+ * Each element in rvecs corresponds to the specific marker in imgPoints.
+ * @param tvecs array of output translation vectors (e.g. std::vector<cv::Vec3d>).
+ * Each element in tvecs corresponds to the specific marker in imgPoints.
+ *
+ * This function receives the detected markers and returns their pose estimation respect to
+ * the camera individually. So for each marker, one rotation and translation vector is returned.
+ * The returned transformation is the one that transforms points from each marker coordinate system
+ * to the camera coordinate system.
+ * The marker corrdinate system is centered on the middle of the marker, with the Z axis
+ * perpendicular to the marker plane.
+ * The coordinates of the four corners of the marker in its own coordinate system are:
+ * (-markerLength/2, markerLength/2, 0), (markerLength/2, markerLength/2, 0),
+ * (markerLength/2, -markerLength/2, 0), (-markerLength/2, -markerLength/2, 0)
+ */
+CV_EXPORTS_W void estimatePoseSingleMarkers(InputArrayOfArrays corners, float markerLength,
+                                            InputArray cameraMatrix, InputArray distCoeffs,
+                                            OutputArray rvecs, OutputArray tvecs);
+
+
+
+/**
+ * @brief Board of markers
+ *
+ * A board is a set of markers in the 3D space with a common cordinate system.
+ * The common form of a board of marker is a planar (2D) board, however any 3D layout can be used.
+ * A Board object is composed by:
+ * - The object points of the marker corners, i.e. their coordinates respect to the board system.
+ * - The dictionary which indicates the type of markers of the board
+ * - The identifier of all the markers in the board.
+ */
+class CV_EXPORTS_W Board {
+
+    public:
+    /**
+    * @brief Provide way to create Board by passing nessesary data. Specially needed in Python.
+    *
+    * @param objPoints array of object points of all the marker corners in the board
+    * @param dictionary the dictionary of markers employed for this board
+    * @param ids vector of the identifiers of the markers in the board
+    *
+    */
+    CV_WRAP static Ptr<Board> create(InputArrayOfArrays objPoints, const Ptr<Dictionary> &dictionary, InputArray ids);
+    /// array of object points of all the marker corners in the board
+    /// each marker include its 4 corners in CCW order. For M markers, the size is Mx4.
+    CV_PROP std::vector< std::vector< Point3f > > objPoints;
+
+    /// the dictionary of markers employed for this board
+    CV_PROP Ptr<Dictionary> dictionary;
+
+    /// vector of the identifiers of the markers in the board (same size than objPoints)
+    /// The identifiers refers to the board dictionary
+    CV_PROP std::vector< int > ids;
+};
+
+
+
+/**
+ * @brief 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 (@sa drawPlanarBoard)
+ */
+class CV_EXPORTS_W GridBoard : public Board {
+
+    public:
+    /**
+     * @brief Draw a GridBoard
+     *
+     * @param outSize size of the output image in pixels.
+     * @param img output image with the board. The size of this image will be outSize
+     * and the board will be on the center, keeping the board proportions.
+     * @param marginSize minimum margins (in pixels) of the board in the output image
+     * @param borderBits width of the marker borders.
+     *
+     * This function return the image of the GridBoard, ready to be printed.
+     */
+    CV_WRAP void draw(Size outSize, OutputArray img, int marginSize = 0, int borderBits = 1);
+
+
+    /**
+     * @brief Create a GridBoard object
+     *
+     * @param markersX number of markers in X direction
+     * @param markersY number of markers in Y direction
+     * @param markerLength marker side length (normally in meters)
+     * @param markerSeparation separation between two markers (same unit as markerLength)
+     * @param dictionary dictionary of markers indicating the type of markers
+     * @param firstMarker id of first marker in dictionary to use on board.
+     * @return the output GridBoard object
+     *
+     * This functions creates a GridBoard object given the number of markers in each direction and
+     * the marker size and marker separation.
+     */
+    CV_WRAP static Ptr<GridBoard> create(int markersX, int markersY, float markerLength,
+                                         float markerSeparation, const Ptr<Dictionary> &dictionary, int firstMarker = 0);
+
+    /**
+      *
+      */
+    CV_WRAP Size getGridSize() const { return Size(_markersX, _markersY); }
+
+    /**
+      *
+      */
+    CV_WRAP float getMarkerLength() const { return _markerLength; }
+
+    /**
+      *
+      */
+    CV_WRAP float getMarkerSeparation() const { return _markerSeparation; }
+
+
+    private:
+    // number of markers in X and Y directions
+    int _markersX, _markersY;
+
+    // marker side lenght (normally in meters)
+    float _markerLength;
+
+    // separation between markers in the grid
+    float _markerSeparation;
+};
+
+
+
+/**
+ * @brief Pose estimation for a board of markers
+ *
+ * @param corners vector of already detected markers corners. For each marker, its four corners
+ * are provided, (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers, the
+ * dimensions of this array should be Nx4. The order of the corners should be clockwise.
+ * @param ids list of identifiers for each marker in corners
+ * @param board layout of markers in the board. The layout is composed by the marker identifiers
+ * and the positions of each marker corner in the board reference system.
+ * @param cameraMatrix input 3x3 floating-point camera matrix
+ * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$
+ * @param distCoeffs vector of distortion coefficients
+ * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
+ * @param rvec Output vector (e.g. cv::Mat) corresponding to the rotation vector of the board
+ * (@sa Rodrigues). Used as initial guess if not empty.
+ * @param tvec Output vector (e.g. cv::Mat) corresponding to the translation vector of the board.
+ * Used as initial guess if not empty.
+ *
+ * This function receives the detected markers and returns the pose of a marker board composed
+ * by those markers.
+ * A Board of marker has a single world coordinate system which is defined by the board layout.
+ * The returned transformation is the one that transforms points from the board coordinate system
+ * to the camera coordinate system.
+ * Input markers that are not included in the board layout are ignored.
+ * The function returns the number of markers from the input employed for the board pose estimation.
+ * Note that returning a 0 means the pose has not been estimated.
+ */
+CV_EXPORTS_W int estimatePoseBoard(InputArrayOfArrays corners, InputArray ids, const Ptr<Board> &board,
+                                   InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec,
+                                   OutputArray tvec);
+
+
+
+
+/**
+ * @brief Refind not detected markers based on the already detected and the board layout
+ *
+ * @param image input image
+ * @param board layout of markers in the board.
+ * @param detectedCorners vector of already detected marker corners.
+ * @param detectedIds vector of already detected marker identifiers.
+ * @param rejectedCorners vector of rejected candidates during the marker detection process.
+ * @param cameraMatrix optional input 3x3 floating-point camera matrix
+ * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$
+ * @param distCoeffs optional vector of distortion coefficients
+ * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
+ * @param minRepDistance minimum distance between the corners of the rejected candidate and the
+ * reprojected marker in order to consider it as a correspondence.
+ * @param errorCorrectionRate rate of allowed erroneous bits respect to the error correction
+ * capability of the used dictionary. -1 ignores the error correction step.
+ * @param checkAllOrders Consider the four posible corner orders in the rejectedCorners array.
+ * If it set to false, only the provided corner order is considered (default true).
+ * @param recoveredIdxs Optional array to returns the indexes of the recovered candidates in the
+ * original rejectedCorners array.
+ * @param parameters marker detection parameters
+ *
+ * This function tries to find markers that were not detected in the basic detecMarkers function.
+ * First, based on the current detected marker and the board layout, the function interpolates
+ * the position of the missing markers. Then it tries to find correspondence between the reprojected
+ * markers and the rejected candidates based on the minRepDistance and errorCorrectionRate
+ * parameters.
+ * If camera parameters and distortion coefficients are provided, missing markers are reprojected
+ * using projectPoint function. If not, missing marker projections are interpolated using global
+ * homography, and all the marker corners in the board must have the same Z coordinate.
+ */
+CV_EXPORTS_W void refineDetectedMarkers(
+    InputArray image,const  Ptr<Board> &board, InputOutputArrayOfArrays detectedCorners,
+    InputOutputArray detectedIds, InputOutputArrayOfArrays rejectedCorners,
+    InputArray cameraMatrix = noArray(), InputArray distCoeffs = noArray(),
+    float minRepDistance = 10.f, float errorCorrectionRate = 3.f, bool checkAllOrders = true,
+    OutputArray recoveredIdxs = noArray(), const Ptr<DetectorParameters> &parameters = DetectorParameters::create());
+
+
+
+/**
+ * @brief Draw detected markers in image
+ *
+ * @param image input/output image. It must have 1 or 3 channels. The number of channels is not
+ * altered.
+ * @param corners positions of marker corners on input image.
+ * (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers, the dimensions of
+ * this array should be Nx4. The order of the corners should be clockwise.
+ * @param ids vector of identifiers for markers in markersCorners .
+ * Optional, if not provided, ids are not painted.
+ * @param borderColor color of marker borders. Rest of colors (text color and first corner color)
+ * are calculated based on this one to improve visualization.
+ *
+ * Given an array of detected marker corners and its corresponding ids, this functions draws
+ * the markers in the image. The marker borders are painted and the markers identifiers if provided.
+ * Useful for debugging purposes.
+ */
+CV_EXPORTS_W void drawDetectedMarkers(InputOutputArray image, InputArrayOfArrays corners,
+                                      InputArray ids = noArray(),
+                                      Scalar borderColor = Scalar(0, 255, 0));
+
+
+
+/**
+ * @brief Draw coordinate system axis from pose estimation
+ *
+ * @param image input/output image. It must have 1 or 3 channels. The number of channels is not
+ * altered.
+ * @param cameraMatrix input 3x3 floating-point camera matrix
+ * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$
+ * @param distCoeffs vector of distortion coefficients
+ * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
+ * @param rvec rotation vector of the coordinate system that will be drawn. (@sa Rodrigues).
+ * @param tvec translation vector of the coordinate system that will be drawn.
+ * @param length length of the painted axis in the same unit than tvec (usually in meters)
+ *
+ * Given the pose estimation of a marker or board, this function draws the axis of the world
+ * coordinate system, i.e. the system centered on the marker/board. Useful for debugging purposes.
+ */
+CV_EXPORTS_W void drawAxis(InputOutputArray image, InputArray cameraMatrix, InputArray distCoeffs,
+                           InputArray rvec, InputArray tvec, float length);
+
+
+
+/**
+ * @brief Draw a canonical marker image
+ *
+ * @param dictionary dictionary of markers indicating the type of markers
+ * @param id identifier of the marker that will be returned. It has to be a valid id
+ * in the specified dictionary.
+ * @param sidePixels size of the image in pixels
+ * @param img output image with the marker
+ * @param borderBits width of the marker border.
+ *
+ * This function returns a marker image in its canonical form (i.e. ready to be printed)
+ */
+CV_EXPORTS_W void drawMarker(const Ptr<Dictionary> &dictionary, int id, int sidePixels, OutputArray img,
+                             int borderBits = 1);
+
+
+
+/**
+ * @brief Draw a planar board
+ * @sa _drawPlanarBoardImpl
+ *
+ * @param board layout of the board that will be drawn. The board should be planar,
+ * z coordinate is ignored
+ * @param outSize size of the output image in pixels.
+ * @param img output image with the board. The size of this image will be outSize
+ * and the board will be on the center, keeping the board proportions.
+ * @param marginSize minimum margins (in pixels) of the board in the output image
+ * @param borderBits width of the marker borders.
+ *
+ * This function return the image of a planar board, ready to be printed. It assumes
+ * the Board layout specified is planar by ignoring the z coordinates of the object points.
+ */
+CV_EXPORTS_W void drawPlanarBoard(const Ptr<Board> &board, Size outSize, OutputArray img,
+                                  int marginSize = 0, int borderBits = 1);
+
+
+
+/**
+ * @brief Implementation of drawPlanarBoard that accepts a raw Board pointer.
+ */
+void _drawPlanarBoardImpl(Board *board, Size outSize, OutputArray img,
+                          int marginSize = 0, int borderBits = 1);
+
+
+
+/**
+ * @brief Calibrate a camera using aruco markers
+ *
+ * @param corners vector of detected marker corners in all frames.
+ * The corners should have the same format returned by detectMarkers (see #detectMarkers).
+ * @param ids list of identifiers for each marker in corners
+ * @param counter number of markers in each frame so that corners and ids can be split
+ * @param board Marker Board layout
+ * @param imageSize Size of the image used only to initialize the intrinsic camera matrix.
+ * @param cameraMatrix Output 3x3 floating-point camera matrix
+ * \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$ . If CV\_CALIB\_USE\_INTRINSIC\_GUESS
+ * and/or CV_CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
+ * initialized before calling the function.
+ * @param distCoeffs Output vector of distortion coefficients
+ * \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
+ * @param rvecs Output vector of rotation vectors (see Rodrigues ) estimated for each board view
+ * (e.g. std::vector<cv::Mat>>). That is, each k-th rotation vector together with the corresponding
+ * k-th translation vector (see the next output parameter description) brings the board pattern
+ * from the model coordinate space (in which object points are specified) to the world coordinate
+ * space, that is, a real position of the board pattern in the k-th pattern view (k=0.. *M* -1).
+ * @param tvecs Output vector of translation vectors estimated for each pattern view.
+ * @param stdDeviationsIntrinsics Output vector of standard deviations estimated for intrinsic parameters.
+ * Order of deviations values:
+ * \f$(f_x, f_y, c_x, c_y, k_1, k_2, p_1, p_2, k_3, k_4, k_5, k_6 , s_1, s_2, s_3,
+ * s_4, \tau_x, \tau_y)\f$ If one of parameters is not estimated, it's deviation is equals to zero.
+ * @param stdDeviationsExtrinsics Output vector of standard deviations estimated for extrinsic parameters.
+ * Order of deviations values: \f$(R_1, T_1, \dotsc , R_M, T_M)\f$ where M is number of pattern views,
+ * \f$R_i, T_i\f$ are concatenated 1x3 vectors.
+ * @param perViewErrors Output vector of average re-projection errors estimated for each pattern view.
+ * @param flags flags Different flags  for the calibration process (see #calibrateCamera for details).
+ * @param criteria Termination criteria for the iterative optimization algorithm.
+ *
+ * This function calibrates a camera using an Aruco Board. The function receives a list of
+ * detected markers from several views of the Board. The process is similar to the chessboard
+ * calibration in calibrateCamera(). The function returns the final re-projection error.
+ */
+CV_EXPORTS_AS(calibrateCameraArucoExtended) double calibrateCameraAruco(
+    InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr<Board> &board,
+    Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+    OutputArrayOfArrays rvecs, OutputArrayOfArrays tvecs,
+    OutputArray stdDeviationsIntrinsics, OutputArray stdDeviationsExtrinsics,
+    OutputArray perViewErrors, int flags = 0,
+    TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON));
+
+
+/** @brief It's the same function as #calibrateCameraAruco but without calibration error estimation.
+ */
+CV_EXPORTS_W double calibrateCameraAruco(
+  InputArrayOfArrays corners, InputArray ids, InputArray counter, const Ptr<Board> &board,
+  Size imageSize, InputOutputArray cameraMatrix, InputOutputArray distCoeffs,
+  OutputArrayOfArrays rvecs = noArray(), OutputArrayOfArrays tvecs = noArray(), int flags = 0,
+  TermCriteria criteria = TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 30, DBL_EPSILON));
+
+
+//! @}
+}
+}
+
+#endif