Stereo Matching with Supplementary Boundary Information

Stereo matching, which estimates the disparity of corresponding points in paired images, has problems with accuracy degraded by occlusion, repeated texture, texture-free areas, and gloss. To address this problem, we focused on object boundary information, which is less susceptible to such problems. This is because occlusion is more likely to occur at the boundaries, and even if the corresponding points disappear due to occlusion, the boundaries still have the corresponding parts. The boundary information is also robust to such problems because it is not affected by repeated textures, untextured areas, or gloss. Therefore, we propose a method for generating the boundary ground truth from the depth ground truth and develop a network and loss function for estimating the boundary information. We also propose that the accuracy can be improved by incorporating the estimated boundary information into a state-of-the-art network as an auxiliary.