Line segment matching: A benchmark

As the vital procedure for exploiting line segments extracted from images for solving computer vision problems, Line Segment Matching (LSM) has received growing attentions from researcher in recent years, and a considerable number of methods have been proposed. However, no one has attempted to solve two major problems in this area. The first is how to evaluate different methods in an unbiased way. All proposed methods were evaluated using images and line segment detectors selected by the authors themselves, making the conclusions based on the somewhat biased experiments less convincing. The second problem is that there is no reliably automatic way to access the correctness of obtained line segment matches, which can often be up to hundreds in quantity. Checking them one by one by visual inspection is the only reliable, but very tedious and error-prone way. In this paper, we target to solve the two problems. We introduce a benchmark which provides the ground truth matches among 30 pairs of line segment sets extracted from 15 representative image pairs using two state-of-the-art line segment detectors. With the benchmark, we evaluated some of the existing LSM methods.