Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization

Thomas Holzmann, Michael Maurer, Friedrich Fraundorfer, Horst Bischof; Proceedings of the European Conference on Computer Vision (ECCV), 2018, pp. 468-483

Abstract


We propose a method for urban 3D reconstruction, which incorporates semantic information and plane priors within the reconstruction process in order to generate visually appealing 3D models. We introduce a plane detection algorithm using 3D lines, which detects a more complete and less spurious plane set compared to point-based methods in urban environments. Further, the proposed normalized visibility-based energy formulation eases the combination of several energy terms within a tetrahedra occupancy labeling algorithm and, hence, is well suited for combining it with class specific smoothness terms. As a result, we produce visually appealing and detailed building models (i.e., straight edges and planar surfaces) and a smooth reconstruction of the surroundings.

Related Material


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[bibtex]
@InProceedings{Holzmann_2018_ECCV,
author = {Holzmann, Thomas and Maurer, Michael and Fraundorfer, Friedrich and Bischof, Horst},
title = {Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
month = {September},
year = {2018}
}