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Bayesian graph-cut optimization for wall surfaces reconstruction in indoor environments

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Abstract

In this paper, a new method capable to extract the wall openings (windows and doors) of interior scenes from point clouds under cluttered and occluded environments is presented. For each wall surface extracted by the polyhedral model of a room, our method constructs a cell complex representation, which is used for the wall object segmentation using a graph-cut method. We evaluate the results of the proposed approach on real-world 3D scans of indoor environments and demonstrate its validity.

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Authors and Affiliations

  1. Department of Informatics, University of Zurich, Binzmhlestr. 14, 8050, Zurich, Switzerland

    Georgios-Tsampikos Michailidis & Renato Pajarola

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  1. Georgios-Tsampikos Michailidis
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  2. Renato Pajarola
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Correspondence to Georgios-Tsampikos Michailidis.

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Michailidis, GT., Pajarola, R. Bayesian graph-cut optimization for wall surfaces reconstruction in indoor environments. Vis Comput 33, 1347–1355 (2017). https://doi.org/10.1007/s00371-016-1230-3

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  • DOI: https://doi.org/10.1007/s00371-016-1230-3

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