A SEMI-AUTOMATED APPROACH TO MODEL ARCHITECTURAL ELEMENTS IN SCAN-TO-BIM PROCESSES

被引:3
|
作者
Roman, O. [1 ,2 ]
Avena, M. [1 ,3 ]
Farella, E. M. [1 ]
Remondino, F. [1 ]
Spano, A. [3 ]
机构
[1] Bruno Kessler Fdn FBK, Opt Metrol Unit 3D 3DOM, Trento, Italy
[2] Univ Trento, Dept Ind Engn DII, Trento, Italy
[3] Politecn Torino, Dept Architecture & Design, Turin, Italy
关键词
HBIM; Scan-to-BIM; Parametric modelling; Machine Learning; POINT CLOUD;
D O I
10.5194/isprs-archives-XLVIII-M-2-2023-1345-2023
中图分类号
K85 [文物考古];
学科分类号
0601 ;
摘要
In the last years, the AEC (Architecture, Engineering and Construction) domain has exponentially increased the use of BIM and HBIM models for several applications, such as planning renovation and restoration, building maintenance, cost managing, or structural/energetic retrofit design. However, obtaining detailed as-built BIM models is a demanding and time-consuming process. Especially in historical contexts, many different and complex architectural elements need to be carefully and manually modelled. Meshes or surfaces and NURBS or polylines, derived from 3D reality-based data, are recently used as a reference for the HBIM accurate modelling. This work proposes a comprehensive and novel semi-automated approach to reconstruct architectural elements through the Visual Programming Language (VPL) Dynamo software and a Boundary-Representation method (B-rep), starting from 3D surveying data and point clouds classification. A wide package of scripts provides solutions for modelling complex shapes and transferring the obtained 3D models into BIM Authoring tools for a complete reconstruction phase. The presented procedure, useful for different BIM or HBIM applications, proved to reduce the modelling time significantly.
引用
收藏
页码:1345 / 1352
页数:8
相关论文
共 50 条
  • [21] EXTENDED REALITY AND INFORMATIVE MODELS FOR THE ARCHITECTURAL HERITAGE: FROM SCAN-TO-BIM PROCESS TO VIRTUAL AND AUGMENTED REALITY
    Banfi, Fabrizio
    Brumana, Raffaella
    Stanga, Chiara
    VIRTUAL ARCHAEOLOGY REVIEW, 2019, 10 (21): : 14 - 30
  • [22] Guided optimization of ToxPi model weights using a Semi-Automated approach
    Fleming, Jonathon F.
    House, John S.
    Chappel, Jessie R.
    Motsinger-Reif, Alison A.
    Reif, David M.
    COMPUTATIONAL TOXICOLOGY, 2024, 29
  • [23] Semi-Automated Approach for Retinal Tissue Differentiation
    Kegeles, Evgenii
    Perepelkina, Tatiana
    Baranov, Petr
    TRANSLATIONAL VISION SCIENCE & TECHNOLOGY, 2020, 9 (10): : 1 - 15
  • [24] PERFORMING A VIRTUAL CROSSMATCH: A SEMI-AUTOMATED APPROACH
    Gasiewski, Allison
    Morlen, Ryan
    Heron, Steven D.
    Huang, Yanping
    Kneib, Carolina
    Monos, Dimitri S.
    HUMAN IMMUNOLOGY, 2017, 78 : 170 - 170
  • [25] A Semi-Automated Approach for Anatomical Ontology Mapping
    Petrov, Peter
    Krachunov, Milko
    Vassilev, Dimitar
    JOURNAL OF INTEGRATIVE BIOINFORMATICS, 2013, 10 (02):
  • [26] Semi-automated Tool Recommender for Software Development Processes
    Pilar, Marina
    Simmonds, Jocelyn
    Astudillo, Hernan
    ELECTRONIC NOTES IN THEORETICAL COMPUTER SCIENCE, 2014, 302 : 95 - 109
  • [27] CorDet: Corner-Aware 3D Object Detection Networks for Automated Scan-to-BIM
    Xu, Yongzhi
    Shen, Xuesong
    Lim, Samsung
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2021, 35 (03)
  • [28] A Scan-to-BIM Approach for the Management of Two Arab-Norman Churches in Palermo (Italy)
    Arico, Manuela
    Lo Brutto, Mauro
    Maltese, Antonino
    HERITAGE, 2023, 6 (02): : 1622 - 1644
  • [29] A semi-automated method for dynamic model abstraction
    Lee, K
    Fishwick, PA
    ENABLING TECHNOLOGY FOR SIMULATION SCIENCE, 1997, 3083 : 31 - 41
  • [30] RCrane: semi-automated RNA model building
    Keating, Kevin S.
    Pyle, Anna Marie
    ACTA CRYSTALLOGRAPHICA SECTION D-BIOLOGICAL CRYSTALLOGRAPHY, 2012, 68 : 985 - 995