Recently, 3D Gaussian Splatting (3DGS) has garnered significant attention. However, the unstructured nature of 3DGS poses challenges for large-scale surface reconstruction from aerial images. To address this gap, we propose the first large-scale surface reconstruction method for multi-view stereo (MVS) aerial images based on 3DGS, named Aerial Gaussian Splatting (AGS). Initially, we introduce a data chunking method tailored for large-scale aerial imagery, making the modern 3DGS technology feasible for surface reconstruction over extensive scenes. Additionally, we integrate the Ray-Gaussian Intersection method to obtain normal and depth information, facilitating geometric constraints. Finally, we introduce a multi-view geometric consistency constraint to enhance global geometric consistency and improve reconstruction accuracy. Our experiments on multiple datasets demonstrate for the first time that the GS-based technique can match traditional aerial MVS methods on geometric accuracy, and beat state-of-the-art GS-based methods on geometry and rendering quality.
最近，3D 高斯点喷射（3DGS）引起了广泛关注。然而，3DGS 的非结构化特性给大规模表面重建带来了挑战。为了填补这一空白，我们提出了首个基于 3DGS 的大规模多视角立体（MVS）航拍图像表面重建方法，命名为 Aerial Gaussian Splatting（AGS）。首先，我们引入了一种针对大规模航拍图像的数据分块方法，使现代 3DGS 技术能够在广阔场景中进行表面重建。此外，我们集成了 Ray-Gaussian Intersection 方法，以获取法线和深度信息，便于几何约束。最后，我们引入了多视角几何一致性约束，以提高全局几何一致性和重建精度。我们的实验表明，GS 基础技术首次在几何精度上与传统航拍 MVS 方法相匹配，并在几何和渲染质量上超越了最先进的 GS 基础方法。