Exploring Rapid 3D Heritage Asset Documentation: A Comparative Study of Laser Scanning and NeRF Algorithms in Museum Reconstruction

This paper explores the use of digital techniques for rapid surveys in cultural heritage, focusing on the creation of virtual environments for educational purposes. It compares two prominent methods for 3D reconstruction: laser scanning and AI-enhanced photogrammetry, particularly Neural Radiance Fields (NeRF). The case study centers on the virtual reconstruction of the Eccel Kreuzer Museum in Bolzano, South Tyrol, which involved documenting its original layout before an exhibition change. The research evaluates the performance of the Leica BLK laser scanner against the NeRF-based 3D models generated from video footage captured with an Insta360 ONE camera. While laser scanning provides high-quality results, the NeRF method, leveraging AI-based algorithms, offers a faster, cost-effective solution, particularly in environments with reflective surfaces and confined spaces. Despite challenges in accuracy and computational demands, the AI approach proves suitable for rapid documentation, especially when precision is less critical. The study highlights the advantages and limitations of both techniques, contributing to the ongoing development of 3D digital heritage assets that balance speed, cost, and quality in various applications such as VR and AR educational environments.