Multi-light multi-view surface reconstruction integrated into heritage workflows
Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows
Computer Vision and Pattern Recognition
Summary
It can be hard to capture detailed 3D shapes of cultural heritage objects using photos because normal methods don’t use special lighting information. The authors bring together advanced computer vision tools that use many photos taken under different lighting and angles to better capture surface details. They put these tools into an easy-to-use open software framework commonly used by heritage professionals. This helps archaeologists and conservators get higher-quality 3D models without needing complicated new hardware or software.
What this means in practice
- •For heritage conservators: Create more detailed 3D models of artifacts using existing multi-light image sets within user-friendly open-source tools.
- •For museum imaging teams: Integrate multi-angle and multi-light image processing into current workflows to enhance surface detail capture without new acquisition equipment.
Authors
Baptiste Brument, Robin Bruneau, Benjamin Coupry, Vincent Demoulin, Jean Mélou, Antoine Laurent, Fabien Castan, Jean-Denis Durou, Lilian Calvet
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.