Improving Border Localization of Multi-Baseline Stereo Using Border-Cut

摘要

This paper presents a novel algorithm that improves the localization of disparity discontinuities of disparity maps obtained by multi-baseline stereo. Rather than associating a disparity label to every pixel of a disparity map, it associates a position to every disparity discontinuity. This formulation allows us to find an approximate solution to a 2D labeling problem with robust smoothing term by minimizing multiple 1D problems, thus making possible the use of dynamic programming. Dynamic programming allows the efficient computation of the visibility of most of the cameras during the minimization. The proposed algorithm is not a stereo matcher on it own since it requires an initial disparity map. Nevertheless, it is a very effective way of improving the border localization of disparity maps obtained from a large class of stereo matchers. Whilst the proposed minimization strategy is particularly suitable for stereo with occlusion, it may be used for other labeling problems.