Converts a rotation matrix to a rotation vector or vice versa

dst = cv.Rodrigues(src)
[dst,jacobian] = cv.Rodrigues(src)

Input

• src Input rotation vector (3x1 or 1x3) or rotation matrix (3x3). Both single and double-precision floating-point types are supported.

Output

• dst Output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. Same data type as src.
• jacobian Optional output Jacobian matrix, 3x9 or 9x3, which is a matrix of partial derivatives of the output array components with respect to the input array components. Same data type as src.

The function transforms a rotation matrix in the following way:

theta <- norm(r)
r <- r/theta
R = cos(theta) * I + (1 - cos(theta)) * r * r^T + sin(theta) * A
A = [0, -rz, ry; rz, 0, -rx; -ry, rx, 0]

Inverse transformation can be also done easily, since

sin(theta) * A = (R - R^T) / 2

A rotation vector is a convenient and most compact representation of a rotation matrix (since any rotation matrix has just 3 degrees of freedom). The representation is used in the global 3D geometry optimization procedures like cv.calibrateCamera, cv.stereoCalibrate, or cv.solvePnP.