遇见数据集

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

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DataCite Commons2025-12-02 更新2026-01-03 收录
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This repository contains the I/O data for the project <strong>"</strong>Semi-Automated Indoor Geometry Reconstruction for Daylight Simulation<strong>."</strong>Unzip the content of the zip file in the 'evaluation' sub-folder in the code repository (see references) to have the full data-code package.<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.

提供机构:
4TU.ResearchData
创建时间:
2025-12-02
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