Updated solvePnPRansac()

modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst

@@ -596,7 +596,7 @@ solvePnPRansac
 ------------------
 Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
 
-.. ocv:function:: void solvePnPRansac( InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int iterationsCount = 100, float reprojectionError = 8.0, int minInliersCount = 100, OutputArray inliers = noArray(), int flags = ITERATIVE )
+.. ocv:function:: void solvePnPRansac( InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int iterationsCount = 100, float reprojectionError = 8.0, float confidence = 0.99, OutputArray inliers = noArray(), int flags = ITERATIVE )
 
 .. ocv:pyfunction:: cv2.solvePnPRansac(objectPoints, imagePoints, cameraMatrix, distCoeffs[, rvec[, tvec[, useExtrinsicGuess[, iterationsCount[, reprojectionError[, minInliersCount[, inliers[, flags]]]]]]]]) -> rvec, tvec, inliers
 
@@ -618,15 +618,18 @@ Finds an object pose from 3D-2D point correspondences using the RANSAC scheme.
 
     :param reprojectionError: Inlier threshold value used by the RANSAC procedure. The parameter value is the maximum allowed distance between the observed and computed point projections to consider it an inlier.
 
-    :param minInliersCount: Number of inliers. If the algorithm at some stage finds more inliers than ``minInliersCount`` , it finishes.
+    :param confidence: The probability that the algorithm produces a useful result.
 
     :param inliers: Output vector that contains indices of inliers in ``objectPoints`` and ``imagePoints`` .
 
     :param flags: Method for solving a PnP problem (see  :ocv:func:`solvePnP` ).
 
 The function estimates an object pose given a set of object points, their corresponding image projections, as well as the camera matrix and the distortion coefficients. This function finds such a pose that minimizes reprojection error, that is, the sum of squared distances between the observed projections ``imagePoints`` and the projected (using
-:ocv:func:`projectPoints` ) ``objectPoints``. The use of RANSAC makes the function resistant to outliers. The function is parallelized with the TBB library.
+:ocv:func:`projectPoints` ) ``objectPoints``. The use of RANSAC makes the function resistant to outliers.
 
+.. note::
+
+   * An example of how to use solvePNPRansac for object detection can be found at opencv_source_code/samples/cpp/tutorial_code/calib3d/real_time_pose_estimation/
 
 
 findFundamentalMat