Zum Inhalt springen
Technische Universität München

Spatial Computing

Members

Foto von Florian Noichl

Florian Noichl

Foto von Syed Salman Ahmed

M.Sc. Syed Salman Ahmed

Foto von Nayun Kim

Nayun Kim

Scope

At Spatial Computing, we bridge the physical and digital domains of the built environment through innovative computational approaches. Our expertise includes geometry processing, AI-driven data enrichment, and multi-modal sensor fusion, enabling us to create and update various digital representations tailored to specific needs. This targeted approach contributes to efficient solutions for use cases across disciplines and granularities, from urban planning to facility management.

Projects

Projectstatus
GeoAI4Retrofitongoing

2024

  • Collins, F.; Noichl, F.; Pan, Y.; Carrara, A.; Mafipour, M. S.; Forth, K.; Borrmann, A.: Bestandserfassung mithilfe von Computer Vision Methoden – 18. In: Haghsheno, S.; Satzger, G.; Lauble, S.; Vössing, M. (Hrsg.): Künstliche Intelligenz im Bauwesen. Springer Fachmedien Wiesbaden, 2024, 309-326 mehr…
  • Collins, F.C.; Noichl, F.; Slepicka, M.; Cones, G.; Borrmann, A.: 360-Degree Tri-Modal Scanning: Engineering a Modular Multi-Sensor Platform for Semantic Enrichment of BIM Models. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., 2024 mehr…
  • Noichl, F.; Collins, F. C.; Braun, A.; Borrmann, A.: Enhancing point cloud semantic segmentation in the data-scarce domain of industrial plants through synthetic data. Computer-Aided Civil and Infrastructure Engineering 39 (10), 2024, 1530-1549 mehr…
  • Noichl, F.; Collins, F. C.; Pan, Y.; Mafipour, M.S.; Mehranfar, M.; Borrmann, A.: From Purpose to Technology: A Requirements-Driven Approach to Designing Digital Twin Implementations – 5. In: Jebelli, Houtan; Asadi, Somayeh; Mutis, Ivan; Liu, Rui; Cheng, Jack (Hrsg.): Digital Twins in Construction and the Built Environment. American Society of Civil Engineers, 2024, 91-130 mehr…
  • Noichl, F.; Lichti, D. D.; Borrmann, A.: Automating adaptive scan planning for static laser scanning in complex 3D environments. Automation in Construction 165, 2024, 10551 mehr…
  • Noichl, F.; Stuecke, M.; Thielen, C.; Borrmann, A.: Assessing and Improving Automated Viewpoint Planning for Static Laser Scanning Using Optimization Methods. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., 2024 mehr…

2023

  • Forth, K.; Noichl, F.; Borrmann, A.: LCA Calculation of Retrofitting Scenarios using Geometric Model Reconstruction and Semantic Enrichment of Point Clouds and Images. Proc. of the ASCE International Conference on Computing in Civil Engineering 2023, 2023 mehr…
  • Mafipour, M.S.; Ahmed, D.; Vilgertshofer, S.; Borrmann, A.: Digitalization of 2D Bridge Drawings Using Deep Learning Models. Proc. of the 30th Int. Conference on Intelligent Computing in Engineering (EG-ICE), 2023 mehr…
  • Noichl, F.; Esser, S.; Schlenger, J.: Adaptive scan planning for 4D-BIM-based construction progress monitoring. Proc. of the 34th Forum Bauinformatik, 2023 mehr…
  • Noichl, F.; Pan, Y.; Mafipour, M. S.; Braun, A.; Brilakis, I.; Borrmann, A.: From enriched point cloud to structural and MEP models: An automated approach to create semantic-geometric models for industrial facilities. Proc. of the ASCE International Conference on Computing in Civil Engineering, 2023 mehr…

2022

  • Koleva, B.; Dugstad, A.; Noichl, F.: UAV path planning for photogrammetric capture of buildings towards disaster scenarios. Proceedings of 33. Forum Bauinformatik, 2022 mehr…
  • Noichl, F.; Borrmann, A.: Towards Multicriterial Scan Planning in Complex 3D Environments. Proc. of the Int. Conf. on Computing in Civil and Building Engineering (ICCCBE), 2022 mehr…
  • Noichl, F.; Borrmann, A.: Automated Deterministic Model-based Indoor Scan Planning. Proc. of European Conference on Product and Process Modeling 2022, 2022 mehr…
  • Pan, Yuandong; Noichl, Florian; Braun, Alexander; Borrmann, André; Brilakis, Ioannis: Automatic Creation and Enrichment of 3D Models for Pipe Systems by Co-registration of Laser-scanned Point Clouds and Photos. Proceedings of the 2022 European Conference on Computing in Construction, 2022 mehr…
  • Selimovic, E.; Noichl, F.; Forth, K.; Borrmann, A.: Retrofitting Potential of Building envelopes Based on Semantic Surface Models Derived From Point Clouds. Journal of Facade Design and Engineering 10 (2), 2022, 127-139 mehr…

2021

  • Collins, F.; Mafipour, MS.; Noichl, F.; Pan, Y.; Vega Torres, M. A.: Towards applicable Scan-to-BIM and Scan-to-Floorplan: An end-to-end experiment. Proc. of the 32th Forum Bauinformatik, 2021 mehr…
  • Eickeler, F.; Noichl, F.: Pogo Sampling: How to best preserve information during manual point cloud labeling. Proc. of the 32th Forum Bauinformatik, 2021 mehr…
  • Noichl, F.; Braun, A.; Borrmann, A.: "BIM-to-Scan" for Scan-to-BIM: Generating Realistic Synthetic Ground Truth Point Clouds based on Industrial 3D Models. Proceedings of the 2021 European Conference on Computing in Construction, 2021 mehr…
  • Vega Torres, M.A.; Braun, A.; Noichl, F.; Borrmann, A.; Bauer, H.; Wohlfeld, D.: Recognition of temporary vertical objects in large point clouds of construction sites. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction 174 (4), 2021, 134-149 mehr…
  • Vega, M.; Braun, A.; Bauer, H.; Noichl, F.; Borrmann, A.: Efficient Vertical Object Detection in Large High-Quality Point Clouds of Construction Sites. Proc. of the 2021 European Conference on Computing in Construction, 2021 mehr…
To top