The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 267–274, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-267-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 267–274, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-267-2021

  30 Jun 2021

30 Jun 2021

TOPOLOGY-AWARE 3D MODELLING OF INDOOR SPACES FROM POINT CLOUDS

H. Zavar1, H. Arefi1, S. Malihi2, and M. Maboudi2 H. Zavar et al.
  • 1School of Surveying and Geospatial Eng., College of Eng., University of Tehran, Iran
  • 2Institute of Geodesy and Photogrammetry, Technische Universität Braunschweig, Germany

Keywords: Point Cloud, Indoor Modelling, Data-Driven, B-Rep, Adjacency Graph, Topology, α-shape

Abstract. In this paper we introduce a topology-aware data-driven approach for 3D reconstruction of indoor spaces, which is an active research topic with several practical applications. After separating floor and ceiling, segmentation is followed by computing the α-shapes of the segment. The adjacency graph of all α-shapes is used to find the intersecting planes. By employing a B-rep approach, an initial 3D model is computed. Afterwards, adjacency graph of the intersected planes which constitute the initial model is analyzed in order to refine the 3D model. This leads to a water-tight and topologically correct 3D model. The performance of our proposed approach is qualitatively and quantitatively evaluated on an ISPRS benchmark data set. On this dataset, we achieved 77% completeness, 53% correctness and 1.7–5 cm accuracy with comparison of the final 3D model to the ground truth.