Blumenthal-Barby, D.C.D.C.Blumenthal-BarbyEisert, P.P.Eisert2022-03-042022-03-042014https://publica.fraunhofer.de/handle/publica/23583310.1016/j.cag.2013.12.0012-s2.0-84892176460We propose a binocular stereo method which is optimized for reconstructing surface detail and exploits the high image resolutions of current digital cameras. Our method occupies a middle ground between stereo algorithms focused on depth layering of cluttered scenes and multi-view "object reconstruction" approaches which require a higher view count. It is based on global non-linear optimization of continuous scene depth rather than discrete pixel disparities. We propose a mesh-based data-term for large images, and a smoothness term using robust error norms to allow detailed surface geometry. We show that the continuous optimization approach enables interesting extensions beyond the core algorithm: Firstly, with small changes to the data-term camera parameters instead of depth can be optimized in the same framework. Secondly, we argue that our approach is well suited for a semi-interactive reconstruction work-flow, for which we propose several tools.en006journal article