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    Automated 3D Wireframe Modeling of Indoor Structures from Point Clouds Using Constrained Least-Squares Adjustment for As-Built BIM

    Source: Journal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 004
    Author:
    Jaehoon Jung
    ,
    Sungchul Hong
    ,
    Sanghyun Yoon
    ,
    Jeonghyun Kim
    ,
    Joon Heo
    DOI: 10.1061/(ASCE)CP.1943-5487.0000556
    Publisher: American Society of Civil Engineers
    Abstract: Automated three-dimensional (3D) modeling of building interiors for an as-built building information model (BIM) incurs critical difficulties because of the complex design of indoor structures and a variety of clutter from scanned point clouds. This paper proposes a scheme for automated 3D geometric modeling of indoor structures, including detailed components such as windows and open doors. Moreover, to produce a regularized model, we imposed constrained least-squares adjustment according to an assumption made with respect to typical indoor structures: walls, ceiling, floor, doors, and windows are composed of straight lines, either parallel or orthogonal. Modeling proceeds in two main phases: wall modeling and window modeling. In the wall modeling phase, the point-cloud acquisitions are projected onto a 2D binary image and the wall boundary is traced out. The boundary is regularized by means of the constrained least-squares method, and, thereby, a 2D floor boundary map can be obtained that later produces, by incorporation of a RANdom sample consensus-based height estimation, a 3D wall model. In the window modeling phase, the wall points are each projected onto a 2D inverse binary image to detect the hollow parts, after which image-based filtering removes incorrect detections. The lines, representing the four window edges, are extracted and adjusted again using the constrained least-squares method. Finally, the window models are projected back onto the original coordinates, and the complete 3D wireframe model is obtained. Two typical indoor environments, a seminar room and a corridor, both at Yonsei University, were chosen as study sites. The generated 3D wireframe models were evaluated by comparison with total station measurements. The 3D positional accuracies of the two results were 0.068 and 0.059 m, respectively, at the 90% confidence level, which indicates the effectiveness of the proposed approach. Finally, using the automatically produced wireframe model as a reference, as-built BIM creation was conducted in the BIM software.
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      Automated 3D Wireframe Modeling of Indoor Structures from Point Clouds Using Constrained Least-Squares Adjustment for As-Built BIM

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    contributor authorJaehoon Jung
    contributor authorSungchul Hong
    contributor authorSanghyun Yoon
    contributor authorJeonghyun Kim
    contributor authorJoon Heo
    date accessioned2017-05-08T22:35:35Z
    date available2017-05-08T22:35:35Z
    date copyrightJuly 2016
    date issued2016
    identifier other50904876.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/83209
    description abstractAutomated three-dimensional (3D) modeling of building interiors for an as-built building information model (BIM) incurs critical difficulties because of the complex design of indoor structures and a variety of clutter from scanned point clouds. This paper proposes a scheme for automated 3D geometric modeling of indoor structures, including detailed components such as windows and open doors. Moreover, to produce a regularized model, we imposed constrained least-squares adjustment according to an assumption made with respect to typical indoor structures: walls, ceiling, floor, doors, and windows are composed of straight lines, either parallel or orthogonal. Modeling proceeds in two main phases: wall modeling and window modeling. In the wall modeling phase, the point-cloud acquisitions are projected onto a 2D binary image and the wall boundary is traced out. The boundary is regularized by means of the constrained least-squares method, and, thereby, a 2D floor boundary map can be obtained that later produces, by incorporation of a RANdom sample consensus-based height estimation, a 3D wall model. In the window modeling phase, the wall points are each projected onto a 2D inverse binary image to detect the hollow parts, after which image-based filtering removes incorrect detections. The lines, representing the four window edges, are extracted and adjusted again using the constrained least-squares method. Finally, the window models are projected back onto the original coordinates, and the complete 3D wireframe model is obtained. Two typical indoor environments, a seminar room and a corridor, both at Yonsei University, were chosen as study sites. The generated 3D wireframe models were evaluated by comparison with total station measurements. The 3D positional accuracies of the two results were 0.068 and 0.059 m, respectively, at the 90% confidence level, which indicates the effectiveness of the proposed approach. Finally, using the automatically produced wireframe model as a reference, as-built BIM creation was conducted in the BIM software.
    publisherAmerican Society of Civil Engineers
    titleAutomated 3D Wireframe Modeling of Indoor Structures from Point Clouds Using Constrained Least-Squares Adjustment for As-Built BIM
    typeJournal Paper
    journal volume30
    journal issue4
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/(ASCE)CP.1943-5487.0000556
    treeJournal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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