Abstract This paper presents a novel method for matching line segments between stereo images. Given the fundamental matrix, the local homography can be over determined with pairwise line segment candidates. We exploit this constraint to initialize the candidate and construct the novel homography graph. Because the constraint between the node is based on the epipolar geometry, the homography graph is invariant to the local projective transformation. We employ the reweighted random walk on the graph to rank the candidate, then, we propose the constrained-greedy algorithm to obtain the reliable match. To the best of our knowledge, this is the first study to embed the epipolar geometry into the graph matching theory for the line segment matching. When evaluated on the 32 image patches, our method outperformed the state of the art methods, especially in the scenes of the wide baseline, steep viewpoint changes and dense line segments. The proposed algorithm is available at https://github.com/weidong-whu/line-match-RRW .

中文翻译：

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通过单应图上的重加权随机游走进行稳健的线段匹配

摘要 本文提出了一种新的立体图像线段匹配方法。给定基本矩阵，局部单应性可以通过成对线段候选来过度确定。我们利用这个约束来初始化候选并构建新的单应图。因为节点之间的约束是基于对极几何的，所以单应图对局部射影变换是不变的。我们在图上使用重新加权的随机游走对候选者进行排名，然后，我们提出了约束贪婪算法来获得可靠匹配。据我们所知，这是第一次将对极几何嵌入到线段匹配的图匹配理论中的研究。当对 32 个图像块进行评估时，我们的方法优于最先进的方法，特别是在宽基线、陡峭的视点变化和密集的线段的场景中。建议的算法可在 https://github.com/weidong-whu/line-match-RRW 获得。