Softferns for homography estimation
Shaoguo Liu, Haibo Wang, Jixia Zhang, Franck Davoine, Chunhong Pan · 2011
Ferns was recently proposed to address the problem of fast keypoint matching [1]. In estimating homography, it often yields many similar matching scores under large viewpoint change or when the object is highly repetitive. However, we observe that keypoints having similar scores are usually far away from each other. Based on this fact, we propose a Softferns approach, in which Ferns and homography can alternatively refine each other. Extensive experiments prove that Softferns is a very general improvement over Ferns.