Comparative Visualization of Bim Geometry and Corresponding Point Clouds

Comparative Visualization of Bim Geometry and Corresponding Point Clouds

V. Stojanovic R. Richter J. Döllner M. Trapp

Computer Graphics Systems Chair, Hasso Plattner Institute, University of Potsdam, Germany

Page: 
12-23
|
DOI: 
https://doi.org/10.2495/SDP-V13-N1-12-23
Received: 
N/A
|
Accepted: 
N/A
|
Published: 
1 January 2018
| Citation

OPEN ACCESS

Abstract: 

BIM Level 2, as defined by the UK government, sets out processes and standards that formalise and regulate the collaborative methods for producing, sharing and exchanging information during different stages of any construction project. For overseas organisations that are looking to invest in the UK construction market, they will most certainly need to consider developing their understanding and ability related to BIM in order to enable developing their capability and competency to compete. This paper presents a case study that focuses on the implementation of collaborative based BIM workflow at a large Chinese engineering and construction organisation, which has recently established operations in the UK. The BIM implementation has been achieved under a Knowledge Exchange Partnership framework between the organisation and an academic institution in the UK. The main aim for this partnership project was to transform the organisation’s traditional workflow to achieve a BIM based collaborative workflow, and to comply with BIM Level 2 requirements. The case study has been achieved by adopting an action research methodology, whereby the project affiliate was an active part of the implementation project and was managing and coordinating the partnership project between the organisation and academic partner. Results to date from the project will be documented in this paper. This includes highlighting key challenges, adopted strategies and tactics to overcome the obstacles, pockets of improvements and potential areas for future development.

Keywords: 

3D BIM, 3D visualization, deviation analysis, facility management, point clouds

1. Introduction
2. Related Work
3. Visualization of Point Clouds and 3d Geometry Data
4. Results and Discussion
5. Conclusions
Acknowledgements
  References

[1] Gledson, B., Greenwood, D., Routledge, P., Watson, R. & Woddy, P., Preparing to work in level 2 BIM: an innovative approach to a training and project-based learning, 2016.

[2] Levoy, M. & Whitted, T. The use of points as a display primitive. University of North Carolina, Department of Computer Science, 1985.

[3] Tang, P., Huber, D., Akinci, B., Lipman, R. & Lytle, A. Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques. Automation in Construction, 19(7), pp. 829–843, 2010. https://doi.org/10.1016/j.autcon.2010.06.007

[4] Lee, S.K., An, H.K. & Yu, J.H., An extension of the technology acceptance model for BIM-based FM. In Construction Research Congress 2012: Construction Challenges in a Flat World, pp. 602–611, 2012.

[5] Roper, O.K. & Payant, P.K., The facility management handbook. AMACOM, 2009.

[6] Eastman, C.M., Teicholz, P., Sacks, R. & Liston, K., BIM handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors. In BIM Handbook, John Wiley & Sons, Hoboken, New Jersey, pp. 170–171, 2011.

[7] Kensek, K., BIM guidelines inform facilities management databases: a case study over time. Buildings, 5(3), pp. 899–916, 2015. https://doi.org/10.3390/buildings5030899

[8] Ebbesen, P., Information technology in facilities management-a literature review. EuroFM, (1.4), 2015.

[9] Muñoz, V. & Arayici, Y., Using free tools to support the BIM coordination process into SMEs. Building Information Modelling (BIM) in Design, Construction and Operations, 149, pp. 33–41, 2015.

[10] Kincaid, D., Integrated facility management. Facilities, 12(8), pp. 20–23, 1994. https://doi.org/10.1108/02632779410062353

[11] Ibrahim, K.F., Abanda, F.H., Vidalakis, C. & Woods, G., BIM for FM: input versus output data, 2016.

[12] Woo, J. H. BIM (building information modeling) and pedagogical challenges. In Proceedings of the 43rd ASC National Annual Conference, pp. 12–14, 2006.

[13] Fischer, M., Haymaker, J. & Liston, K., Benefits of 3D and 4D models for facility managers and AEC service providers. 4D CAD and visualization in construction developments and applications, pp. 1–32, 2003.

[14] Lee, W.L., Tsai, M.H., Yang, C.H., Juang, J.R. & Su, J.Y., V3DM+: BIM interactive collaboration system for facility management. Visualization in Engineering, 4(1), 2016. https://doi.org/10.1186/s40327-016-0035-9

[15] Atazadeh, B., Kalantari, M., Rajabifard, A., Ho, S., & Champion, T., Extending a BIMbased data model to support 3D digital management of complex ownership spaces. IJGIS, pp. 1–24, 2016.

[16] Laing, R., Leon, M., Isaacs, J. & Georgiev, D. Scan to BIM: the development of a clear workflow for the incorporation of point clouds within a BIM environment. WIT Transactions on the Built Environment, 149, pp. 279–289, 2015. https://doi.org/10.2495/BIM150241

[17] Dimitrov, A. & Golparvar-Fard, M., Segmentation of building point cloud models including detailed architectural/structural features and MEP systems. Automation in Construction, 51, pp. 32–45, 2015. https://doi.org/10.1016/j.autcon.2014.12.015

[18] Fadli, F., Barki, H., Boguslawski, P. & Mahdjoubi, L., 3D scene capture: a comprehensive review of techniques and tools for efficient Life Cycle Analysis (LCA) and Emergency Preparedness (EP) applications. WIT Transactions on the Built Environment, 149, pp. 85–96, 2015.

[19] Qu, T., & Sun, W., Usage of 3D point cloud data in BIM (Building Information Modelling): Current Applications and Challenges, 2015.

[20] Tuttas, S., Braun, A., Borrmann, A. & Stilla, U., Acquisition and consecutive registration of photogrammetric point clouds for construction progress monitoring using a 4D BIM. PFG, 85(1), pp. 3–15, 2017.

[21] Barki, H., Fadli, F., Shaat, A., Boguslawski, P. & Mahdjoubi, L., BIM models generation from 2D CAD drawings and 3D scans: an analysis of challenges and opportunities for AEC practitioners. Building Information Modelling (BIM) in Design, Construction and Operations, 149, pp. 369–380, 2015.

[22] Anil, E.B., Tang, P., Akinci, B. & Huber, D. Assessment of quality of as-is building information models generated from point clouds using deviation analysis. In Proceedings of SPIE, 2011.

[23] Kalasapudi, V.S., Turkan, Y. & Tang, P., Toward automated spatial change analysis of MEP components using 3D point clouds and as-designed BIM models. In 3DV (Vol. 2, pp. 145–152). IEEE, 2014.

[24] Shneiderman, B., The eyes have it: A task by data type taxonomy for information visualizations. In Visual Languages, 1996. Proceedings., IEEE Symposium, pp. 336–343, 1996.

[25] Semmo, A., Trapp, M., Kyprianidis, J. E. & Döllner, J., Interactive visualization of generalized virtual 3D city models using level-of-abstraction transitions. Computer Graphics Forum 2012, 31(3), pp. 885–894, 2012. https://doi.org/10.1111/j.1467-8659.2012.03081.x

[26] Diakité, A.A. & Zlatanova, S., Valid space description in BIM for 3D Indoor. IJ3DIM, 5(3), pp. 1–17, 2016. https://doi.org/10.4018/ij3dim.2016070101

[27] BUILDINGSMART. IfcShapeRepresentation, 2017, available at: https://tinyurl.com/k9qk77m. (accessed 29 March, 2017).

[28] Richter, R., Discher, S. & Döllner, J., Out-of-core visualization of classified 3d point clouds. 3D Geoinformation Science, 227–242, 2015. https://doi.org/10.1007/978-3-319-12181-9_14

[29] Richter, R., Kyprianidis, J. E. & Döllner, J., Out-of-Core GPU-based change detection in massive 3D point clouds. Transactions in GIS, 17, pp. 724–741, 2013. https://doi.org/10.1111/j.1467-9671.2012.01362.x

[30] Cignoni, P., Corsini, M. & Ranzuglia, G., Meshlab: an open-source 3d mesh processing system. Ercim News, 73(45–46), p. 6, 2008.

[31] Lamire, P. Qt3D 2.0: The FrameGraph. KDAB, 2015, available at: https://tinyurl.com/lg6n2fs. (accessed 13 February, 2017).

[32] Akenine-Möller, T., Haines, E. & Hoffman, N., Real-time rendering. CRC Press, 2008.

[33] Rusu, R. B. & Cousins, S. 3D is here: Point Cloud Library (PCL). IEEE ICRA, 2011.