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Progressive Model-Driven Approach for 3D Modeling of Indoor Spaces.

Ali Abdollahi1, Hossein Arefi1,2, Shirin Malihi3

  • 1School of Engineering, Faculty of Surveying and Geospatial Engineering, University of Tehran, Tehran 1417614411, Iran.

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Summary

This study presents a model-driven approach for 3D indoor modeling using laser scan data. The method effectively reconstructs building interiors, handling noise and clutter for accurate 3D models.

Keywords:
3D indoor modeling3D reconstructionBIMlaser scanningmodel-drivenpoint cloud

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Area of Science:

  • Computer Vision
  • 3D Reconstruction
  • Geomatics Engineering

Background:

  • 3D indoor modeling is crucial for various applications.
  • Three-dimensional point clouds from laser scanners are widely used for this purpose.
  • Existing methods face challenges with noisy, cluttered, and obstructed data.

Purpose of the Study:

  • To develop a robust method for 3D indoor space modeling.
  • To address data imperfections like obstruction, clutter, and noise.
  • To reconstruct detailed and accurate 3D models of building interiors.

Main Methods:

  • A model-driven approach using watertight predefined models for indoor space reconstruction.
  • A two-step process enabling the modeling of non-rectangular spaces.
  • An improvement step to enhance model detail by incorporating intrusions and protrusions.
  • 3D model generation through 2D to 3D extrusion.

Main Results:

  • The algorithm successfully reconstructs indoor spaces from laser scan point clouds.
  • Achieved completeness ranging from 77% to 95%.
  • Achieved correctness ranging from 85% to 97%.
  • Demonstrated geometric accuracy between 1.7 cm and 2.4 cm.

Conclusions:

  • The proposed model-driven algorithm effectively reconstructs 3D indoor spaces.
  • The method demonstrates high performance in completeness, correctness, and geometric accuracy.
  • Validated with four benchmark real-world datasets, proving its efficacy.