从室内点云中高效可靠的3D语义模型重建建筑物的专业管道
Cedrique Fotsing1, Willy Carlos Tchuitcheu2, Lemopi Isidore Besong3
1Department of Graphic Systems, Institute for Computer Science, Brandenburg University of Technology Cottbus-Senftenberg, Platz der Deutschen Einheit 1, 03046 Cottbus, Germany.
Journal of imaging
|October 25, 2024
概括
本研究介绍了一种自动化管道,用于从点云数据中创建建筑物的3D语义模型. 该方法准确地提取建筑元素,如墙壁和开口,以改善建筑中的3D建模.
科学领域:
- 计算机视觉 计算机视觉
- 三维重建的3D重建
- 建筑信息建模 (BIM) 是指建筑信息建模.
背景情况:
- 激光扫描的进步提供了详细的3D点云.
- 来自点云的多层建筑的自动建模具有挑战性.
研究的目的:
- 开发一种新的管道,用于自动生成多层建筑的3D语义模型.
- 从室内点云层层次上提取建筑组件.
主要方法:
- 建筑组件的分层提取. 建筑组件的分层提取.
- 将点云划分为地板,然后进行墙壁检测.
- 房间,地面和天花板的提取使用投射的墙壁星座.
- 深度学习用于识别墙壁中的门窗.
- 在工业基础课程 (IFC) 格式中生成最终模型.
主要成果:
- 在提取建筑元素时的高精度和回忆.
- 通过广泛的实验证明了有效性和可靠性.
- 在IFC格式中精确生成3D语义模型.
结论:
- 拟议的管道提供了一个有效和准确的解决方案,用于从点云3D语义建模.
- 这项工作为建筑,工程和建筑 (AEC) 行业的点云处理的进步做出了贡献.
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