Semantic Edge Collapse: A Mesh Edge Collapse Algorithm preserving per Face Semantic Information
Recent advancements in 3D data acquisition and processing have enabled high-fidelity urban modeling. Yet, production of structured 3D models in standards like <em>CityGML</em> remain complex, resource-intensive, and difficult to automate. This paper introduces a low-cost alternative that...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-2-W8-2024/185/2024/isprs-archives-XLVIII-2-W8-2024-185-2024.pdf |
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| Summary: | Recent advancements in 3D data acquisition and processing have enabled high-fidelity urban modeling. Yet, production of structured 3D models in standards like <em>CityGML</em> 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. |
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| ISSN: | 1682-1750 2194-9034 |