IFC-based point-cloud information processing method for structural elements

被引：0
|
作者：
Xu Z. [1 ]
Kang R. [1 ]
Sun N. [1 ]
机构：
[1] School of Civil Engineering, Southeast University, Nanjing
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2018年 / 48卷 / 06期
关键词：
Data mapping; IFC(industry foundation classes); Point cloud; Structural elements; Visualization;
D O I：
10.3969/j.issn.1001-0505.2018.06.012
中图分类号：
学科分类号：
摘要：
To realize the process of 3D rapid modeling of existing building structures, a data file processing method is proposed from collecting the original point cloud data to forming the IFC(industry foundation classes)-compliant document. The method can provide a foundation for the Webpage visualization management. After the initial separation and fine cutting process in the processing of the original point cloud data, a denoising method is used to effectively reduce the data size, optimize the spatial mapping relationship in the point cloud model, and support high-quality point cloud surface reconstruction. The surface reconstruction algorithm is applied to complete the generation of intermediate form of OBJ data, which realizes the point-to-surface conversion. Then, an encoding system for building components is proposed to convert the coding and geometric information into the IFC format files. Furthermore, the result is used for web page rendering and information management. The experimental results indicate that the proposed converting and processing method can compress the point-cloud data file, create grid surfaces to realize component substantiation, and finally generate IFC format data files. Thus, the effectiveness and the practicability of the proposed method are proved. © 2018, Editorial Department of Journal of Southeast University. All right reserved.
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页码：1068 / 1075
页数：7
相关论文
共 10 条
  • [1] Deng L., Cheng X., Cheng X., Et al., A method of building information model reconstruction based on point cloud data, Surveying and Mapping of Geology and Mineral Resources, 32, 4, pp. 14-16, (2016)
  • [2] Shi R., Liu H., Wang R., Et al., Study on building ancient architecture information model of Fuxue Hutong 36 <sup>#</sup> Yard , Journal of Beijing University of Civil Engineering and Architecture, 30, 4, pp. 1-7, (2014)
  • [3] Gao T., Akinci B., Ergan S., Et al., An approach to combine progressively captured point clouds for BIM update, Advanced Engineering Informatics, 29, 4, pp. 1001-1012, (2015)
  • [4] Krijnen T., Beetz J., An IFC schema extension and binary serialization format to efficiently integrate point cloud data into building models, Advanced Engineering Informatics, 33, pp. 473-490, (2017)
  • [5] Tang P.B., Huber D., Akinci B., Et al., Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques, Automation in Construction, 19, 7, pp. 829-843, (2010)
  • [6] Lu W., Wan Y., He P., Et al., Extracting and plane segmenting buildings from large scene point cloud, Chinese Journal of Lasers, 42, 9, pp. 344-350, (2015)
  • [7] Armeni I., Sener O., Zamir A.R., Et al., 3D semantic parsing of large-scale indoor spaces, 2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), pp. 1534-1543, (2016)
  • [8] Corsini M., Cignoni P., Scopigno R., Efficient and flexible sampling with blue noise properties of triangular meshes, IEEE Transactions on Visualization and Computer Graphics, 18, 6, pp. 914-924, (2012)
  • [9] Specht A.R., Devy M., Surface segmentation using a modified ball-pivoting algorithm, 2004 International Conference on Image Processing, pp. 1931-1934, (2004)
  • [10] Maiti A., Chakravarty D., Performance analysis of different surface reconstruction algorithms for 3D reconstruction of outdoor objects from their digital images, 5, pp. 932-958, (2016)
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