LiDAR and BIM Integration for 3D Reconstruction and Preservation of Cultural Heritage Images in Ancient Architecture

This study presents an innovative methodology for integrating LiDAR and Building Information Modeling (BIM) to reconstruct and preserve images of cultural heritage in ancient architecture. Leveraging advances in deep learning and computer vision, the research study proposes a comprehensive approach to improve the fidelity and authenticity of reconstructed three-dimensional scenes. The methodology includes LiDAR remote sensing image collection using UAVs, a novel deep learning-based 3D image reconstruction algorithm, and the integration of BIM for visualization and preservation. Experimental evaluation of the proposed methodology demonstrates competitive performance compared to existing methods. Specifically, the Chamfer Distance (CD) metric is used as a standard for evaluation and shows that the proposed approach achieves a median CD value of 0.531, indicating stable and reliable reconstruction results. This research contributes to the advancement of 3D reconstruction techniques for heritage preservation and provides a foundation for future research in this area.