Semantic Edge Collapse: A Mesh Edge Collapse Algorithm preserving per Face Semantic Information

Abstract

Recent advancements in 3D data acquisition and processing have enabled high-fidelity urban modeling. Yet, production of structured 3D models in standards like CityGML remain complex, resource-intensive, and difficult to automate. This paper introduces a low-cost alternative that we call “structured mesh model” designed to cover many applications of structured 3D models at a lower cost. It relies on integrating geometric simplification with segmentation alignment to produce a lightweight, unified mesh representation. Using an edge-collapse algorithm, our method combines geometry from an existing mesh with labeled point cloud data to create a continuous mesh with edges aligned to segmentation boundaries, preserving both geometric fidelity and semantic clarity. The resulting structured mesh efficiently reduces memory requirements while maintaining accuracy, offering a practical solution for simulations and urban analyses that require structured 3D data.