Accelerated RANSAC for 2D homography estimation based on global brightness consistency
Gaku Nakano · 2017
This paper proposes a novel sampling method for accelerating RANSAC family on 2D homography estimation. From the initial set of matched points, the proposed method generates a promising reduced subset having higher inlier ratio than the initial set by utilizing pixel values of the matches. Regarding pairs of the pixel value as two dimensional scattered points, we estimate the global brightness consistency of the pixel values. Then, points that violate the global brightness consistency are removed from the initial point set. Incorporating the proposed method with RANSAC and USAC, we demonstrate that the number of iterations and computational time are both significantly reduced by orders of magnitude while maintaining accuracy of homography estimation.