Introduction

Neural Radiance Fields (NeRF) (1) and 3D Gaussian Splatting (3DGS) (2) have revolutionized the 3D graphics landscape since their introduction, offering unprecedented quality for novel view synthesis (NVS). While these neural representations excel at photorealistic rendering, they have yet to replace traditional mesh-based geometry in mainstream applications. Current game engines have not yet integrated Gaussian Splatting as a standard rendering primitive alongside mesh rasterization, though promising community-driven open-source solutions are emerging (3). The goal is to develop an immersive virtual museum experience that showcases the potential of hybrid rendering techniques. The project will focus on creating a virtual mineralogy museum, where visitors can interact with photorealistic 3D reconstructions of rare earth minerals that are typically too precious or fragile for direct handling in traditional museum settings.

Project specifications

• Scan and reconstruct museum artifacts using 3D Gaussian Splatting techniques.
• Create engaging virtual spaces with thoughtful UX/UI design and interactive gameplay elements (ed- ucational mini-games, guided tours, interactive exhibits).
• Ensure smooth performance and a comfortable user experience in virtual reality environments.

Development Environment

• Unity (C#) OR Unreal Engine (Blueprints / C++)
• VR Development (OpenXR)

Expected Outcome

This project will result in a functional VR museum application that demonstrates the viability of hybrid rendering approaches for cultural heritage preservation and interactive education. The student will gain hands-on experience with cutting-edge 3D reconstruction techniques while developing practical skills in VR, game development, and user experience design.

References

(1) B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng. “NeRF: Repre senting Scenes as Neural Radiance Fields for View Synthesis.” arXiv: 2003.08934 [cs]. (Aug. 3, 2020), [Online]. Available: http://arxiv.org/abs/2003.08934, pre-published.

(2) A. Dalal, D. Hagen, K. G. Robbersmyr, and K. M. Knausg˚ard, “Gaussian Splatting: 3D Reconstruction and Novel View Synthesis, a Review,” IEEE Access, vol. 12, pp. 96 797–96 820, 2024, issn: 2169-3536. doi: 10.1109/ACCESS.2024.3408318. arXiv: 2405.03417 [cs]. [Online]. Available: http://arxiv. org/abs/2405.03417.

(3) “Gaussian Splatting is pretty cool!· Aras’ website,” Aras’ website. (Sep. 5, 2023), [Online]. Available: https://aras-p.info/blog/2023/09/05/Gaussian-Splatting-is-pretty-cool/.