A robust to outliers method for estimating the homography

A novel method robust to outliers is proposed which integrates outliers rejection within the homography estimation pipeline with a negligible computational overhead. With a basis of algebraic criterion, the proposed method has a low level of computational time with an arbitrary large number of key-point correspondences. Given a set of 2D-to-2D matches, we formulate pose estimation problem as a low-rank homogeneous system where the solution lies on its 1D null space. Outlier correspondences are those rows of the linear system which perturb the null space and are progressively detected by projecting them on an iteratively estimated solution of the null space. Several simulations based on synthetic and real image demonstrate that the proposed method can achieve robust homography estimation to different ratios of outliers.