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作 者:王超[1] 王娇颖[1,2] 许开銮 刘楚墙[3] 王志强 WANG Chao;WANG Jiaoying;XU Kailuan;LIU Chuqiang;WANG Zhiqiang(Xi'an Institute of Applied Optics,Xi'an 710065,China;Guangzhou Institute of Technology,Xidian University,Guangzhou 510555,China;School of Geodesy and Geomatics,Wuhan University,Wuhan 430072,China;Wuhan Tianjihang Information Technology Co.Ltd.,Wuhan 430074,China)
机构地区:[1]西安应用光学研究所,西安710065 [2]西安电子科技大学广州研究院,广州510555 [3]武汉大学测绘学院,武汉430072 [4]武汉天际航信息科技股份有限公司,武汉430074
出 处:《测绘科学》2023年第10期159-168,共10页Science of Surveying and Mapping
基 金:国防基础科研计划项目(JCKY2021208B023)。
摘 要:针对当前BIM与实景三维模型融合过程中空间位置配准精度较低的问题,该文提出了一种借助真实激光点云的BIM模型与实景三维模型融合的方法。研究选取大场景和小场景两种样例数据,首先基于BIM实体几何信息转换和三角化加密的方法生成了BIM模型建筑物点云,其次基于增量式SFM算法和立体像对密集匹配方法先后生成实景环境下的稀疏和稠密点云,最后基于ISS特征提取结合改进ICP算法的完成了不同模型下点云和真实激光点云的配准。结果显示,该方法能够有效地实现BIM模型与实景三维场景信息融合,对新型智慧城市建设、工程建设智慧化管理具有一定意义。In response to the problem of low spatial position registration accuracy in the current fusion process between building information modeling(BIM)models and real-life 3D models, the article proposes a method for integrating BIM models with real-life 3D models using real laser point clouds. The study selected two types of sample data: large and small scenes. Firstly, the BIM model building point cloud was generated based on BIM entity geometry information conversion and triangulation encryption methods. Secondly, sparse and dense point clouds were generated in real environment based on incremental structure from motion(SFM) algorithm and stereo pair dense matching method. Finally, the registration of point clouds and real laser point clouds under different models was completed based on intrinsic shape signature(ISS)feature extraction combined with improved iterative closest point(ICP)algorithm. The results show that this method can effectively achieve the fusion of BIM model and real-time 3D scene information, which is of great significance for the construction of new smart cities and intelligent management of engineering construction.
分 类 号:P237[天文地球—摄影测量与遥感]
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