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Bestandserfassung mithilfe von Computer Vision Methoden

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Künstliche Intelligenz im Bauwesen

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Zusammenfassung

In diesem Kapitel werden verschiedene Ansätze für die Bestandserfassung mithilfe von ComputerVision (CV) Methoden dargestellt. Verschiedene Subdomänen von CV, wie beispielsweise semantische oder Instanz-Segmentierung, unterstützen bei der automatischen Anreicherung von semantischen Informationen basierend auf verschiedenen Eingangsdaten. Im ersten Anwendungsfall werden 2D-Zeichnung als Datenquelle verwendet, um geometrische As-Designed-Modelle zu rekonstruieren. Als zweite wichtige Datenquelle werden im zweiten Anwendungsfall räumlich-visuelle Bestandsaufnahmen (Punktwolken und Bilder) betrachtet und deren semantische Extraktionsmethoden vorgestellt.

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Authors and Affiliations

  1. Lehrstuhl für Computergestützte Modellierung und Simulation, TUM School of Engineering and Design, Technische Universität München, München, Deutschland

    Fiona Collins, Florian Noichl, Yuandong Pan, Andrea Carrara, M. Saeed Mafipour, Kasimir Forth & André Borrmann

Authors
  1. Fiona Collins
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  2. Florian Noichl
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  3. Yuandong Pan
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  4. Andrea Carrara
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  5. M. Saeed Mafipour
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  6. Kasimir Forth
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  7. André Borrmann
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Corresponding author

Correspondence to Kasimir Forth .

Editor information

Editors and Affiliations

  1. TMB, Karlsruher Inst. für Technologie (KIT), Karlsruhe, Baden-Württemberg, Deutschland

    Shervin Haghsheno

  2. IISM, Karlsruhe Institute of Technology, Karlsruhe, Baden-Württemberg, Deutschland

    Gerhard Satzger

  3. TMB, Karlsruhe Institute of Technology, Karlsruhe, Deutschland

    Svenja Lauble

  4. IISM, Karlsruher Institut für Technologie, Karlsruhe, Baden-Württemberg, Deutschland

    Michael Vössing

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© 2024 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Collins, F. et al. (2024). Bestandserfassung mithilfe von Computer Vision Methoden. In: Haghsheno, S., Satzger, G., Lauble, S., Vössing, M. (eds) Künstliche Intelligenz im Bauwesen . Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-42796-2_18

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