Stereo reconstruction from dense disparity maps using the locus method

摘要

Abstract: The reconstruction of a surface having already matched corresponding points from stereo images (disparities) is a nontrivial task. This paper presents a new technique, the so-called Locus method, that exploits sensor geometry to efficiently build a terrain representation from stereo disparities. The power of this approach is the efficient and direct computation of a dense elevation map in arbitrary resolution. Additionally it proposes to solve problems like occlusions, ambiguities, and uncertainties caused by stereo matching errors. We extended the Locus method for active range finder data to the stereo disparity mapping case. For this reason, a newly developed fast matching method is utilized that provides dense disparity maps, hence a disparity for each input pixel. Once this data set is given, the Locus method can be applied in a straightforward and efficient way to gain a robust 3D reconstruction of the observed surface. It operates directly in image space, using dense and uniform measurements instead of first converting to object space. Experiments on synthetic and natural environment data show that the Locus method is less sensitive to disparity noise than traditional reconstruction. !5