用3DGS直接测点,精度高且无需专业设备。
Accurate Point Measurement in 3DGS -- A New Alternative to Traditional Stereoscopic-View Based Measurements
- 通过渲染视图对齐点,实现跨视角精准匹配测量
- 在真实数据上达到1-2厘米的误差,薄结构误差减半
- 适合普通用户在网页端操作,无需立体观测训练
3D高斯泼溅(3DGS)虽以实时渲染和高质量新视角合成著称,但其在几何测量中的潜力尚未被充分挖掘。与多视图立体(MVS)点云或网格相比,3DGS生成的视图视觉质量更高、完整性更好。现有测量方法仍依赖昂贵的立体工作站或直接在不完整、不准确的网格上人工选取点。作为新视角合成器,3DGS能精确还原原始视图并平滑插值中间视图,使用户可直观地在不同视图间选取对应点,并通过三角化获得精确的三维坐标。该方法模拟传统立体测量,但显著降低门槛:无需立体工作站或立体视觉能力。同时支持多视角交点(超过两个视图),提升精度。我们开发了基于网页的应用原型,在多个无人机航拍数据集上验证,该方法可在标准硬件上实现与传统立体测量相当甚至更优的精度。定量结果显示,关键点误差在1-2厘米范围;在复杂细长结构上,网格法误差0.062米,本方法降至0.037米;在网格重建失败的尖锐角处,本方法成功测量所有点,误差仅0.013米,而网格法完全失效。代码已开源:https://github.com/GDAOSU/3dgs_measurement_tool。
原文摘要 · Abstract (English)
3D Gaussian Splatting (3DGS) has revolutionized real-time rendering with its state-of-the-art novel view synthesis, but its utility for accurate geometric measurement remains underutilized. Compared to multi-view stereo (MVS) point clouds or meshes, 3DGS rendered views present superior visual quality and completeness. However, current point measurement methods still rely on demanding stereoscopic workstations or direct picking on often-incomplete and inaccurate 3D meshes. As a novel view synthesizer, 3DGS renders exact source views and smoothly interpolates in-between views. This allows users to intuitively pick congruent points across different views while operating 3DGS models. By triangulating these congruent points, one can precisely generate 3D point measurements. This approach mimics traditional stereoscopic measurement but is significantly less demanding: it requires neither a stereo workstation nor specialized operator stereoscopic capability. Furthermore, it enables multi-view intersection (more than two views) for higher measurement accuracy. We implemented a web-based application to demonstrate this proof-of-concept (PoC). Using several UAV aerial datasets, we show this PoC allows users to successfully perform highly accurate point measurements, achieving accuracy matching or exceeding traditional stereoscopic methods on standard hardware. Specifically, our approach significantly outperforms direct mesh-based measurements. Quantitatively, our method achieves RMSEs in the 1-2 cm range on well-defined points. More critically, on challenging thin structures where mesh-based RMSE was 0.062 m, our method achieved 0.037 m. On sharp corners poorly reconstructed in the mesh, our method successfully measured all points with a 0.013 m RMSE, whereas the mesh method failed entirely. Code is available at: https://github.com/GDAOSU/3dgs_measurement_tool.
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