Geometry reconstruction and orthophoto generation from 3D Gaussian Splatting in architectures with thin elements

Abstract. Orthorectified façade imagery and metric 3D models support architectural documentation, conservation, and further analysis. Orthophoto production from standard Structure-from-Motion and Multi-View Stereo (SfM–MVS) pipelines performs well on broad opaque surfaces, but can be challenging on thin, repetitive, and partly transparent elements (e.g., railings, balusters, grilles). Indeed, in the latter cases depth estimation becomes unstable, filtering removes some structures, and meshing priors thicken elements or bridge voids, compromising both geometry generation and orthophoto production. This paper evaluates 3D Gaussian Splatting (3DGS) as a surface-free alternative for metric façade representation and orthophoto generation in such conditions. We propose a compact façade-plane alignment and scale control procedure to render orthographic products. On a real façade dataset acquired under diffuse illumination, we compare a standard SfM–MVS true-orthophoto baseline with three 3DGS workflows: PostShot training with a custom orthographic renderer, Tortho-Gaussian for optimization and orthographic rendering, and Blender rendering of PostShot splats. Quality is assessed, using a laser scanning acquisition as a benchmark, via completeness, edge fidelity and topological preservation. Results indicate that 3DGS better preserves the topological pattern in railing regions, keeping members separated and apertures open, and enables rapid orthographic rendering once trained. SfM–MVS shows better results on large, well-textured wall areas, whereas 3DGS may introduce mild edge softening or halos at high-contrast boundaries.