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Scan-to-BIM for ‘secondary’ building components

Published: 01 August 2018 Publication History

Abstract

Works dealing with Scan-to-BIM have, to date, principally focused on 'structural' components such as floors, ceilings and walls (with doors and windows). But the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components, such as plugs, switches, ducts, and signs. In this paper, we present a new 6D-based (XYZ + RGB) approach that processes dense coloured 3D points provided by terrestrial laser scanners in order to recognize the aforementioned smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, extinguishers and others. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and an original consensus procedure integrates both results in order to infer recognition. Finally, the recognized object is positioned and inserted in the as-is semantically-rich 3D model, or BIM model. The assessment of the method has been carried out in simulated scenarios under virtual scanning providing high recognition rates and precise positioning results. Experimental tests in real indoors using our MoPAD (Mobile Platform for Autonomous Digitization) platform have also yielded promising results.

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        cover image Advanced Engineering Informatics
        Advanced Engineering Informatics  Volume 37, Issue C
        Aug 2018
        175 pages

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        Elsevier Science Publishers B. V.

        Netherlands

        Publication History

        Published: 01 August 2018

        Author Tags

        1. Object recognition
        2. Scan-to-BIM
        3. Automatic BIM
        4. 3D data processing

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        • (2021)A semi-supervised learning detection method for vision-based monitoring of construction sites by integrating teacher-student networks and data augmentationAdvanced Engineering Informatics10.1016/j.aei.2021.10137250:COnline publication date: 1-Oct-2021

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