测试3D高斯点云在人群渲染中的视觉细节感知，优化实时图形性能。
Evaluating CrowdSplat: Perceived Level of Detail for Gaussian Crowds
- 通过双选实验评估高斯点云的视觉质量，控制运动、点数和像素高度三因素。
- 在128个高斯点时达到感知质量与效率的平衡，远低于传统网格渲染。
- 适合虚拟现实与游戏开发者优化人群渲染策略，兼顾画质与性能。
高效且逼真的群体渲染是虚拟现实（VR）和游戏等实时图形应用的关键。以往的多级细节（LOD）表示方法包括多边形网格、基于图像的代理和点云。近期，3D高斯泼溅（3D Gaussian Splatting）被探索用于实时人群渲染。本文开展一项两择一强制选择（2AFC）实验，评估3D高斯化身的感知质量。考察三个因素：运动状态、多级细节（即高斯点数量）、化身像素高度（对应观察距离）。参与者观看成对动画3D高斯化身，需选出更精细的一方。结果可为高斯基人群渲染的LOD策略优化提供依据，帮助实现实时应用中高效渲染与视觉质量的平衡。
原文摘要 · Abstract (English)
Efficient and realistic crowd rendering is an important element of many real-time graphics applications such as Virtual Reality (VR) and games. To this end, Levels of Detail (LOD) avatar representations such as polygonal meshes, image-based impostors, and point clouds have been proposed and evaluated. More recently, 3D Gaussian Splatting has been explored as a potential method for real-time crowd rendering. In this paper, we present a two-alternative forced choice (2AFC) experiment that aims to determine the perceived quality of 3D Gaussian avatars. Three factors were explored: Motion, LOD (i.e., #Gaussians), and the avatar height in Pixels (corresponding to the viewing distance). Participants viewed pairs of animated 3D Gaussian avatars and were tasked with choosing the most detailed one. Our findings can inform the optimization of LOD strategies in Gaussian-based crowd rendering, thereby helping to achieve efficient rendering while maintaining visual quality in real-time applications.
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