Real-Time 3D Reconstruction for the Conservation of the Great Wall’s Cultural Heritage Using Depth Cameras

Abstract

The Great Wall, a pivotal part of Chinese cultural heritage listed on the World Heritage List since 1987, confronts challenges stemming from both natural deterioration and anthropogenic damage. Traditional conservation strategies are impeded by the Wall’s vast geographical spread, substantial costs, and the inefficiencies associated with conventional surveying techniques such as manual surveying, laser scanning, and low-altitude aerial photography. These methods often struggle to capture the Wall’s intricate details, resulting in limitations in field operations and practical applications. In this paper, we propose a novel framework utilizing depth cameras for the efficient real-time 3D reconstruction of the Great Wall. To overcome the challenge of the high complexity of reconstruction, we generate multi-level geometric features from raw depth images for hierarchical computation guidance. On one hand, the local set of sparse features serve as basic cues for multi-view-based reconstruction. On the other hand, the global set of dense features are employed for optimization guidance during reconstruction. The proposed framework facilitates the real-time, precise 3D reconstruction of the Great Wall in the wild, thereby significantly enhancing the capabilities of traditional surveying methods for the Great Wall. This framework offers a novel and efficient digital approach for the conservation and restoration of the Great Wall’s cultural heritage.