List of tools for point cloud to BIM conversion

2025-09-11 2025-09-12 About 800 words 4 minutes

Contents

Study	Multi-storeyᵃ	Slabsᵇ	Non-Manhattan wallsᶜ	Wall surfacesᵈ	Volumetric wallsᵉ	Volumetric spacesᶠ	Opening detectionᵍ	IFC outputʰ	Open-sourceⁱ
Wang et al. [9]	✘	✘	✘	✘	✘	✘	✘	✘	✘
Macher et al. [27]	✘	✔	✔	✔	✘	✘	✘	✘	✘
Jung et al. [20]	✘	✔	✘	✔	✘	✘	✘	✘	✘
Shi et al. [38]	✘	✔	✘	✔	✘	✘	✘	✘	✘
Ochmann et al. [18]	✔	✔	✔	✔	✔	✔	✔	✘	✘
Bassier and Vergauwen [19]	✘	✔	✘	✔	✘	✘	✘	✘	✘
Romero-Jarén and Arranz [8]	✘	✔	✘	✔	✔	✘	✔	✘	✘
Gen and Gentes [52]	✔	✔	✔	✔	✘	✔	✘	✘	✘
Martens and Blankenbach [10]	✘	✔	✘	✔	✘	✘	✘	✘	✘
Mahmoud et al. [11]	✘	✔	✘	✔	✘	✘	✔	✔	✘
Mehranfar et al. [53]	✘	✔	✘	✔	✘	✘	✔	✔	✘
Cloud2BIM	✔	✔	✔	✔	✔	✔	✔	✔	✔

Notes ᵃ Automatic processing of multi-story buildings, where floors are detected and structured hierarchically (e.g., as IfcBuildingStorey) without requiring manual intervention.
ᵇ Detection of slab position, thickness, and horizontal dimensions.
ᶜ Support for walls that are not strictly aligned to an orthogonal (Manhattan) grid, allowing for arbitrary angles.
ᵈ Identification and semantic segmentation of wall surfaces from point clouds.
ᵉ Detection of walls as solid objects, including their topology (connections between walls) and representation as parametric elements with thickness, start and end points, and height.
ᶠ Creation of volumetric room representations, which are derived separately from wall representations and are not necessarily included in solutions that detect volumetric walls.
ᵍ Geometric representation and placement of openings within wall elements, including width, height, position, and type (door, window).
ʰ Automatic conversion of extracted building geometry into the IFC format without reliance on proprietary software.
ⁱ The tool’s code is publicly available, allowing free use and modification.

Tool	Semantic segmentation	Walls and openings detection	Multi-story support	IFC output
Pointfuse/Autodesk Recap	✔	✔	✔ᵃ	✔
Aurivus	✔	✘	✔ᵇ	✔
Faramoon	✘	✔	✘	✔
usBIM.Scan2IFC	✘	✔	✘	✔
Undet	✘	✔ᶜ	✘	✘
ClearEdge3D EdgeWise	✘	✔ᵈ	✘	✘
Geo-Plus VisionBIM	✔	✔ᵉ	✘	✘
BricsCAD BIM	✔	✔	✘	✔
Leica CloudWorx	✘	✔ᶠ	✘	✘

Notes

ᵃ Exports to IFC at LOD100, requiring manual refinement.
ᵇ Multi-story support is available, but users must manually define height levels.
ᶜ Wall and opening detection requires manual selection (Fit function).
ᵈ Walls are detected, but openings are not. Wall detection accuracy is limited.
ᵉ Wall detection is available, but openings are not detected.
ᶠ Wall and opening placement is assisted but requires manual selection.

References

[9] C. Wang, Y.K. Cho, C. Kim, Automatic BIM component extraction from point clouds of existing buildings for sustainability applications, Autom. Constr. 56, http://dx.doi.org/10.1016/j.autcon.2015.04.001.
[27] H. Macher, T. Landes, P. Grussenmeyer, From point clouds to building information models: 3D semi-automatic reconstruction of indoors of existing buildings, Appl. Sci. 7, http://dx.doi.org/10.3390/app7101030.
[20] J. Jung, C. Stachniss, S. Ju, J. Heo, Automated 3D volumetric reconstruction of multiple-room building interiors for as-built BIM, Adv. Eng. Inform. 38, http://dx.doi.org/10.1016/j.aei.2018.10.007.
[38] W. Shi, W. Ahmed, N. Li, W. Fan, H. Xiang, M. Wang, Semantic geometric modelling of unstructured indoor point cloud, ISPRS Int. J. Geo-Inf. 8, http://dx.doi.org/10.3390/ijgi8010009.
[18] S. Ochmann, R. Vock, R. Klein, Automatic reconstruction of fully volumetric 3D building models from oriented point clouds, ISPRS J. Photogramm. Remote Sens. 151, http://dx.doi.org/10.1016/j.isprsjprs.2019.03.017.
[19] M. Bassier, M. Vergauwen, Unsupervised reconstruction of building information modeling wall objects from point cloud data, Autom. Constr. 120, http://dx.doi.org/10.1016/j.autcon.2020.103338.
[8] R. Romero-Jarén, J. Arranz, Automatic segmentation and classification of BIM elements from point clouds, Autom. Constr. 124, http://dx.doi.org/10.1016/j.autcon.2021.103576.
[52] Z. Chen, S. Gentes, From point cloud to as-built BIM: Semi-automated wall reconstruction for dismantling of nuclear power plants, https://robdekon.de/user/data/bibliography/pdf/Chen2021.pdf.
[10] J. Martens, J. Blankenbach, VOX2BIM+- a fast and robust approach for automated indoor point cloud segmentation and building model generation, PFG–J. Photogramm. Remote. Sens. Geoinf. Sci. 91, http://dx.doi.org/10.1007/s41064-023-00243-1.
[11] M. Mahmoud, W. Chen, Y. Yang, Y. Li, Automated BIM generation for large-scale indoor complex environments based on deep learning, Autom. Constr. 162, http://dx.doi.org/10.1016/j.autcon.2024.105376.
[53] M. Mehranfar, A. Braun, A. Borrmann, From dense point clouds to semantic digital models: End-to-end AI-based automation procedure for Manhattan-world structures, Autom. Constr. 162 (2024) 105392, http://dx.doi.org/10.1016/j.autcon.2024.105392.

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