  We propose a novel method for estimating the global rotations of the cameras
independently of their positions and the scene structure. When two calibrated
cameras observe five or more of the same points, their relative rotation can be
recovered independently of the translation. We extend this idea to multiple
views, thereby decoupling the rotation estimation from the translation and
structure estimation. Our approach provides several benefits such as complete
immunity to inaccurate translations and structure, and the accuracy improvement
when used with rotation averaging. We perform extensive evaluations on both
synthetic and real datasets, demonstrating consistent and significant gains in
accuracy when used with the state-of-the-art rotation averaging method.
