Localizing stereo boundaries is difficult because matching cues are absent in the occluded regions that are adjacent to them. We introduce an energy and level-set optimizer that improves boundaries by encoding the essential geometry of occlusions: The spatial extent of an occlusion must equal the amplitude of the disparity jump that causes it. In a collection of figure-ground scenes from Middlebury and Falling Things stereo datasets, the model provides more accurate boundaries than previous occlusion-handling techniques.
@article{arxiv.2006.16094,
title = {Level Set Stereo for Cooperative Grouping with Occlusion},
author = {Jialiang Wang and Todd Zickler},
journal= {arXiv preprint arXiv:2006.16094},
year = {2021}
}
Comments
ICIP 2021 Code and data: https://github.com/jialiangw/levelsetstereo