Robust line matching based on Ray-Point-Ray structure descriptor

Abstract

In this paper, we propose a novel two-view line matching method through converting matching line segments extracted from two uncalibrated images to matching the introduced Ray-Point-Ray (RPR) structures. The method first recovers the partial connectivity of line segments through sufficiently exploiting the gradient map. To efficiently matching line segments, we introduce the Ray-Point-Ray (RPR) structure consisting of a joint point and two rays (line segments) connected to the point. Two sets of RPRs are constructed from the connected line segments extracted from two images. These RPRs are then described with the proposed SIFT-like descriptor for efficient initial matching to recover the fundamental matrix. Based on initial RPR matches and the recovered fundamental matrix, we propose a match propagation scheme consisting of two stages to refine and find more RPR matches. The first stage is to propagate matches among those initially formed RPRs, while the second stage is to propagate matches among newly formed RPRs constructed by intersecting unmatched line segments with those matched ones. In both stages, candidate matches are evaluated by comprehensively considering their descriptors, the epipolar line constraint, and the topological consistency with neighbor point matches. Experimental results demonstrate the good performance of the proposed method as well as its superiority to the state-of-the-art methods.