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.
高效且真实的 crowd 渲染是许多实时图形应用（如虚拟现实（VR）和游戏）中的重要元素。为此，提出并评估了不同的细节层次（LOD）头像表示方法，如多边形网格、基于图像的替代物和点云。最近，3D高斯点云（Gaussian Splatting）被探索作为实时 crowd 渲染的潜在方法。本文介绍了一项二选一强迫选择实验（2AFC），旨在确定3D高斯头像的感知质量。我们探讨了三个因素：运动、LOD（即高斯点数量）以及头像在像素中的高度（对应于视距）。参与者观看了成对的动画3D高斯头像，并选择了细节更丰富的一个。我们的研究结果有助于优化基于高斯的 crowd 渲染中的LOD策略，从而帮助在实时应用中实现高效渲染同时保持视觉质量。