Code for "Semi-Automated Indoor Geometry Reconstruction for Daylight Simulation"

<strong>Note: There is a separate repository that contains the I/O data for evaluation. This is mentioned in the references. </strong><br><strong>Abstract:</strong> This study presents a semi-automated pipeline for reconstructing indoor geometries from point cloud data for daylight simulation. The pipeline generates watertight models of permanent architectural surfaces with window boundaries through three steps: (1) preprocessing, (2) permanent structure reconstruction, and (3) window boundary extraction. The pipeline was evaluated in four rooms of varying complexity against manually reconstructed models, with daylight availability and glare simulations performed in <em>Radiance</em>. Daylight availability results show absolute errors below 10% for UDI, with mean TAI percentage errors within 18% for rooms with rectangular windows and up to 44% for those with non-rectangular windows. The DGP error remains under 4%, and the modelling time does not exceed 5 minutes in any scenario. The approach enables rapid generation of simulation-ready models with acceptable accuracy for CBDM.