Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-10-09

AUTHORS

Thomas Holzmann , Michael Maurer , Friedrich Fraundorfer , Horst Bischof

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. More... »

PAGES

487-503

References to SciGraph publications

  • 2014. Let There Be Color! Large-Scale Texturing of 3D Reconstructions in COMPUTER VISION – ECCV 2014
  • 2014-12. Reconstructing the World’s Museums in INTERNATIONAL JOURNAL OF COMPUTER VISION
  • 2016. Manhattan-World Urban Reconstruction from Point Clouds in COMPUTER VISION – ECCV 2016
  • 2008. Fusion of Feature- and Area-Based Information for Urban Buildings Modeling from Aerial Imagery in COMPUTER VISION – ECCV 2008
  • Book

    TITLE

    Computer Vision – ECCV 2018

    ISBN

    978-3-030-01263-2
    978-3-030-01264-9

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-030-01264-9_29

    DOI

    http://dx.doi.org/10.1007/978-3-030-01264-9_29

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107502729


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