用网格融合高斯点云,实现虚拟现实中更真实物理交互。
GS-Verse: Mesh-based Gaussian Splatting for Physics-aware Interaction in Virtual Reality
- 将3D网格与高斯点云直接结合,提升表面建模精度。
- 18人用户测试显示,拉伸、扭转等操作更真实且一致。
- 不依赖特定物理引擎,适合快速开发与复用现有模型。
随着沉浸式3D内容需求增长,虚拟现实(VR)中直观高效的交互方法愈发重要。当前基于物理的3D内容操控技术常受限于工程复杂度和简化的几何表示(如四面体笼),影响视觉保真度与物理准确性。本文提出GS-Verse(Gaussian Splatting for Virtual Environment Rendering and Scene Editing),通过将物体网格直接融入高斯点云(GS)表示,实现更精确的表面逼近,从而生成高度真实的变形与交互效果。该方法可复用现有3D网格资产,简化开发流程,并支持任意物理引擎,具备强部署灵活性。在包含18名参与者的对比用户研究中,本方法在物理感知拉伸操作上显著优于现有最先进方法,且在扭转、摇晃等其他物理操作中表现更一致。多场景、多交互评估进一步验证其高性能与可靠性,展现出作为现有方法可行替代方案的潜力。
原文摘要 · Abstract (English)
As the demand for immersive 3D content grows, the need for intuitive and efficient interaction methods becomes paramount. Current techniques for physically manipulating 3D content within Virtual Reality (VR) often face significant limitations, including reliance on engineering-intensive processes and simplified geometric representations, such as tetrahedral cages, which can compromise visual fidelity and physical accuracy. In this paper, we introduce GS-Verse (Gaussian Splatting for Virtual Environment Rendering and Scene Editing), a novel method designed to overcome these challenges by directly integrating an object's mesh with a Gaussian Splatting (GS) representation. Our approach enables more precise surface approximation, leading to highly realistic deformations and interactions. By leveraging existing 3D mesh assets, GS-Verse facilitates seamless content reuse and simplifies the development workflow. Moreover, our system is designed to be physics-engine-agnostic, granting developers robust deployment flexibility. This versatile architecture delivers a highly realistic, adaptable, and intuitive approach to interactive 3D manipulation. We rigorously validate our method against the current state-of-the-art technique that couples VR with GS in a comparative user study involving 18 participants. Specifically, we demonstrate that our approach is statistically significantly better for physics-aware stretching manipulation and is also more consistent in other physics-based manipulations like twisting and shaking. Further evaluation across various interactions and scenes confirms that our method consistently delivers high and reliable performance, showing its potential as a plausible alternative to existing methods.
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