中文标题#
CM2LoD3：使用語義衝突圖重建 LoD3 建築模型
英文标题#
CM2LoD3: Reconstructing LoD3 Building Models Using Semantic Conflict Maps
中文摘要#
詳細的 3D 建築模型對於城市規劃、數字孿生和災害管理應用至關重要。 雖然 Level of Detail 1 (LoD) 1 和 LoD2 建築模型廣泛可用，但它們缺乏用於高級城市分析的關鍵立面元素。 相比之下，LoD3 模型通過包含窗戶、門和人行通道等立面元素來解決這一限制。 然而，其生成傳統上需要手動建模，使得大規模採用具有挑戰性。 在本貢獻中， CM2LoD3，我們提出了一種新方法，利用從射線到模型先驗分析中獲得的衝突地圖（CMs）來重建 LoD3 建築模型。 與之前的工作不同，我們專注於使用我們開發的語義衝突地圖生成器（SCMG）生成的合成 CMs 對現實世界的 CMs 進行語義分割。 我們還觀察到，可以通過置信度分數將紋理模型的額外分割與 CMs 融合，以進一步提高分割性能，從而提高 3D 重建精度。 實驗結果表明，我們的 CM2LoD3 方法在分割和重建建築開口方面是有效的，具有 61% 的不確定性感知融合分割建築紋理的性能。 這項研究有助於自動化 LoD3 模型重建的進步，為可擴展和高效的 3D 城市建模鋪平了道路。 我們的項目可用：https://github.com/InFraHank/CM2LoD3
英文摘要#
Detailed 3D building models are crucial for urban planning, digital twins, and disaster management applications. While Level of Detail 1 (LoD)1 and LoD2 building models are widely available, they lack detailed facade elements essential for advanced urban analysis. In contrast, LoD3 models address this limitation by incorporating facade elements such as windows, doors, and underpasses. However, their generation has traditionally required manual modeling, making large-scale adoption challenging. In this contribution, CM2LoD3, we present a novel method for reconstructing LoD3 building models leveraging Conflict Maps (CMs) obtained from ray-to-model-prior analysis. Unlike previous works, we concentrate on semantically segmenting real-world CMs with synthetically generated CMs from our developed Semantic Conflict Map Generator (SCMG). We also observe that additional segmentation of textured models can be fused with CMs using confidence scores to further increase segmentation performance and thus increase 3D reconstruction accuracy. Experimental results demonstrate the effectiveness of our CM2LoD3 method in segmenting and reconstructing building openings, with the 61% performance with uncertainty-aware fusion of segmented building textures. This research contributes to the advancement of automated LoD3 model reconstruction, paving the way for scalable and efficient 3D city modeling. Our project is available: https://github.com/InFraHank/CM2LoD3
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