Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate 3D assets, segmenting Gaussians by class is essential. Existing segmentation approaches are typically limited to certain types of scenes, e.g., ''circular'' scenes, to determine clear object boundaries. However, this method is ineffective when removing large objects in non-''circling'' scenes such as large outdoor scenes. We propose Semantics-Controlled GS (SCGS), a segmentation-driven GS approach, enabling the separation of large scene parts in uncontrolled, natural environments. SCGS allows scene editing and the extraction of scene parts for VR. Additionally, we introduce a challenging outdoor dataset, overcoming the ''circling'' setup. We outperform the state-of-the-art in visual quality on our dataset and in segmentation quality on the 3D-OVS dataset. We conducted an exploratory user study, comparing a 360-video, plain GS, and SCGS in VR with a fixed viewpoint. In our subsequent main study, users were allowed to move freely, evaluating plain GS and SCGS. Our main study results show that participants clearly prefer SCGS over plain GS. We overall present an innovative approach that surpasses the state-of-the-art both technically and in user experience.

本研究针对高斯点云渲染在编辑复杂户外场景时的局限性提出了解决方案。通过引入语义控制的高斯点云方法，研究展示了在非循环场景中分离大型场景部分的能力。最终结果表明，用户对这种新方法在视觉效果和使用体验上都给予了更高的评价。

语义控制的高斯点云在虚拟现实中的户外场景重建和渲染