Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows

2026-09-14

AI Summary

本文解决了文化遗产工作流程中多视角多光照表面重建的问题，通过将先进的计算机视觉方法整合到开源摄影测量框架Meshroom中。

Abstract

Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessible to archaeologists, conservators, and heritage technicians. These tools have been successful for conventional multi-view acquisition, but they do not routinely exploit richer multi-view, multi-light data, despite its potential for improving fine-scale surface reconstruction. This limitation is particularly relevant in heritage contexts, where controlled-light acquisition devices such as RTI domes are already used to capture illumination-varying image sets. The challenge is therefore to connect these existing acquisition practices with recent computer vision methods in a form that can be used within operational heritage workflows. In this work, we address this need by integrating state-of-the-art components from computer vision for multi-view, multi-light surface reconstruction into Meshroom, an open-source photogrammetry framework. Rather than proposing a new reconstruction algorithm, our contribution is to assemble and expose existing advanced methods, namely a complete photometric stereo ecosystem (calibrated, self-calibrated and universal), automatic object masking, and multi-view normal-and-reflectance integration, within a usable heritage-oriented workflow. The proposed system thus provides an intermediate software layer between computer vision research code and practical cultural heritage applications, making recent techniques easier to use and evaluate.

Problem

• multi-view
• multi-light
• surface reconstruction
• cultural heritage

Innovation

• multi-view multi-light surface reconstruction
• photogrammetry
• cultural heritage
• Meshroom
• photometric stereo