On robust rectification for uncalibrated images

We present a robust algorithm performing uncalibrated rectification which does not require explicit computation of the epipolar geometry, and specifically of the fundamental matrix. Our algorithm exploits the fact that the fundamental matrix of a pair of rectified images has a particular known form. This allows us to set up a minimization that yields the rectifying homographies directly from image correspondences. Experimental results show that our method works even in the presence of noise, and can cope with inaccurate point correspondences. Robustness in the presence of wrong point correspondences is also addressed in this paper and a two-step outlier detector is described.