Pose estimation for single markers

[rvecs, tvecs] = cv.estimatePoseSingleMarkers(corners, markerLength, cameraMatrix, distCoeffs)
[rvecs, tvecs, objPoints] = cv.estimatePoseSingleMarkers(...)

Input

• corners cell array of already detected markers corners. For each marker, its four corners are provided, (e.g {{[x,y],..}, ..}). The order of the corners should be clockwise.
• markerLength the length of the markers' side. The returning translation vectors will be in the same unit. Normally, unit is meters.
• cameraMatrix input 3x3 floating-point camera matrix A = [fx 0 cx; 0 fy cy; 0 0 1].
• distCoeffs vector of distortion coefficients [k1,k2,p1,p2,k3,k4,k5,k6,s1,s2,s3,s4] of 4, 5, 8 or 12 elements.

Output

• rvecs cell array of output rotation vectors (e.g. {[x,y,z], ...}). Each element in rvecs corresponds to the specific marker in corners.
• tvecs cell array of output translation vectors (e.g. {[x,y,z], ...}). Each element in tvecs corresponds to the specific marker in corners.
• objPoints optional output, array of object points of the marker four corners (object points for the system centered in a single marker given the marker length, see explanation below).

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)