Finds an object pose from 3D-2D point correspondences using the RANSAC scheme

[rvec, tvec, inliers] = cv.solvePnPRansac(objectPoints, imagePoints, cameraMatrix)
[...] = cv.solvePnPRansac(..., 'OptionName', optionValue, ...)

Input

• objectPoints Array of object points in the object coordinate space, 1xNx3/Nx1x3 or Nx3 array, where N is the number of points, or cell array of length N of 3-element vectors can be also passed here {[x,y,z], ...}.
• imagePoints Array of corresponding image points, 1xNx2/Nx1x2 or Nx2 array, where N is the number of points, or cell array of length N of 2-element vectors can be also passed here {[x,y], ...}.
• cameraMatrix Input camera matrix A = [fx 0 cx; 0 fy cy; 0 0 1].

Output

• rvec Output rotation vector (see cv.Rodrigues) that, together with tvec, brings points from the model coordinate system to the camera coordinate system.
• tvec Output translation vector.
• inliers Output vector that contains indices of inliers in objectPoints and imagePoints.

Options

• DistCoeffs Input vector of distortion coefficients [k1,k2,p1,p2,k3,k4,k5,k6,s1,s2,s3,s4,taux,tauy] of 4, 5, 8, 12 or 14 elements. If the vector is empty, the zero distortion coefficients are assumed. default empty.
• Rvec Initial rvec. Not set by default.
• Tvec Initial tvec. Not set by default.
• UseExtrinsicGuess Parameter used for Method='Iterative'. If true, the function uses the provided rvec and tvec values as initial approximations of the rotation and translation vectors, respectively, and further optimizes them. default false.
• IterationsCount Number of iterations. default 100.
• 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. default 8.0.
• Confidence The probability that the algorithm produces a useful result. default 0.99
• Method Method for solving the PnP problem. See cv.solvePnP. default 'Iterative'

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 cv.projectPoints) objectPoints. The use of RANSAC makes the function resistant to outliers.