Semi-Global Matching (SGM) is a widely-used efficient
\nstereo matching technique. It works well for textured
\nscenes, but fails on untextured slanted surfaces due to its
\nfronto-parallel smoothness assumption. To remedy this
\nproblem, we propose a simple extension, termed SGM-P, to
\nutilize precomputed surface orientation priors. Such priors
\nfavor different surface slants in different 2D image regions
\nor 3D scene regions and can be derived in various
\nways. In this paper we evaluate plane orientation priors derived
\nfrom stereo matching at a coarser resolution and show
\nthat such priors can yield significant performance gains for
\ndifficult weakly-textured scenes. We also explore surface
\nnormal priors derived from Manhattan-world assumptions,
\nand we analyze the potential performance gains using oracle
\npriors derived from ground-truth data. SGM-P only
\nadds a minor computational overhead to SGM and is an
\nattractive alternative to more complex methods employing
\nhigher-order smoothness terms.<\/p>\n","protected":false},"excerpt":{"rendered":"
Semi-Global Matching (SGM) is a widely-used efficient stereo matching technique. It works well for textured scenes, but fails on untextured slanted surfaces due to its fronto-parallel smoothness assumption. To remedy this problem, we propose a simple extension, termed SGM-P, to utilize precomputed surface orientation priors. Such priors favor different surface slants in different 2D image […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"International Conference on 3D Vision (3DV), 2017","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"International Conference on 3D Vision (3DV), 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