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Real-time collaborative reconstruction of digital building models with mobile devices

Franz, Steffen ; Irmler, Robert ; Rüppel, Uwe :
Real-time collaborative reconstruction of digital building models with mobile devices.
[Online-Edition: http://www.sciencedirect.com/science/article/pii/S1474034617...]
In: Advanced Engineering Informatics, 38 569 - 580. ISSN 1474-0346
[Artikel] , (2018)

Offizielle URL: http://www.sciencedirect.com/science/article/pii/S1474034617...

Kurzbeschreibung (Abstract)

Many software-based building processes require digital building models. Since the building stock does not have sufficient data in this regard, the demand for Scan-to-BIM processes is increasing. In this paper we present a system for the reconstruction of ‘as-built’ BIM content of house interiors based on the Google Tango technology. The strength of our approach is the use of low-cost mobile scanning devices and a client-server system that allows for a real-time collaborative scanning and reconstruction of indoor scenes. We developed a server application that continuously aggregates scan data of multiple scanning devices (clients) and applies the data stream to a real-time post-processing pipeline to reconstruct rooms, walls, doors and windows. The reconstruction result is then distributed to all clients, where it is visualized in real time. The collaborative workflow and real-time data processing make our system especially useful in situations that are time-critical and require concurrent collection and processing of data. One of our targeted use cases therefore is the model generation for crime scene documentation. The effectiveness of our approach was demonstrated on three test sites. Our results compare well to other state-of-art methods regarding the reconstruction of walls, but they also revealed potential for improvement regarding the detection of doors and windows in occluded and cluttered environments.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Franz, Steffen ; Irmler, Robert ; Rüppel, Uwe
Titel: Real-time collaborative reconstruction of digital building models with mobile devices
Sprache: Englisch
Kurzbeschreibung (Abstract):

Many software-based building processes require digital building models. Since the building stock does not have sufficient data in this regard, the demand for Scan-to-BIM processes is increasing. In this paper we present a system for the reconstruction of ‘as-built’ BIM content of house interiors based on the Google Tango technology. The strength of our approach is the use of low-cost mobile scanning devices and a client-server system that allows for a real-time collaborative scanning and reconstruction of indoor scenes. We developed a server application that continuously aggregates scan data of multiple scanning devices (clients) and applies the data stream to a real-time post-processing pipeline to reconstruct rooms, walls, doors and windows. The reconstruction result is then distributed to all clients, where it is visualized in real time. The collaborative workflow and real-time data processing make our system especially useful in situations that are time-critical and require concurrent collection and processing of data. One of our targeted use cases therefore is the model generation for crime scene documentation. The effectiveness of our approach was demonstrated on three test sites. Our results compare well to other state-of-art methods regarding the reconstruction of walls, but they also revealed potential for improvement regarding the detection of doors and windows in occluded and cluttered environments.

Titel der Zeitschrift, Zeitung oder Schriftenreihe: Advanced Engineering Informatics
Band: 38
Verlag: Elsevier
Freie Schlagworte: Scan-to-BIM, Collaboration, Mobile devices, Google Tango, Building Information Modeling, Industry Foundation Classes
Fachbereich(e)/-gebiet(e): 13 Fachbereich Bau- und Umweltingenieurwissenschaften
13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Numerische Methoden und Informatik im Bauwesen
Hinterlegungsdatum: 14 Dez 2018 09:50
DOI: https://doi.org/10.1016/j.aei.2018.08.012
Offizielle URL: http://www.sciencedirect.com/science/article/pii/S1474034617...
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