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arXiv · 2409.00381

3D Gaussian Splatting for Large-scale Surface Reconstruction from Aerial Images

YuanZheng Wu·Jin Liu·Shunping Ji
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Abstract

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel 3DGS-based method for large-scale surface reconstruction using aerial multi-view stereo (MVS) images, named Aerial Gaussian Splatting (AGS). First, we introduce a data chunking method tailored for large-scale aerial images, making 3DGS feasible for surface reconstruction over extensive scenes. Second, we integrate the Ray-Gaussian Intersection method into 3DGS to obtain depth and normal information. Finally, we implement multi-view geometric consistency constraints to enhance the geometric consistency across different views. Our experiments on multiple datasets demonstrate, for the first time, the 3DGS-based method can match conventional aerial MVS methods on geometric accuracy in aerial large-scale surface reconstruction, and our method also beats state-of-the-art GS-based methods both on geometry and rendering quality.

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YuanZheng Wu, Jin Liu, Shunping Ji. 2024-08-31. 3D Gaussian Splatting for Large-scale Surface Reconstruction from Aerial Images. https://arxiv.org/abs/2409.00381

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