Twofold consensus for boundary detection ground truth

In the evaluation of boundary detection methods it is common to use as ground truth a set of boundary images that are hand-made by human experts. This work proposes a novel representation of this ground truth. More specifically, we propose to combine the hand-made boundary images into a set-based consensus, which is constructed from the concordances and discordances among the images. We study the theoretical and visual properties of this consensus and present an application to boundary image quality evaluation.