Abstract
The Building Industry (BI) lacks in sharing information among different and heterogeneous stakeholders. With the advent of new technologies such as mobile devices, IoT and Industry 4.0 different approaches have been introduced, but it is still an open research field. The present essay aims at moving a step forward using augmented reality connected with the Building Information Modelling (BIM) methodology enhancing the effectiveness of process in the BI.
The authors improved the Fraunhofer Italia’s AR4Construction (AR4C) mobile application, that lets construction workers visualize the BIM model of a building on site in augmented reality and interact with its design information. The main purpose of this study consists in studying and developing an indoor location functionality for the AR4C application. The research focuses on understanding the starting point and the orientation of the user, through the application of 3D mathematical structures and computer vision methods.
The result is a core module for an indoor location functionality. We have evaluated distances and orientation errors, analyzing the results according to the implementation strategy. In conclusion, possible improvements have been analyzed within this paper, which offers a first approach for visualization-only based frameworks aiming at indoor location and navigation and using BIM models as a starting point.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Schweigkofler, A., Monizza, G.P., Domi, E., Popescu, A., Ratajczak, J., Marcher, C., Riedl, M., Matt, D.: Development of a digital platform based on the integration of augmented reality and BIM for the management of information in construction processes. In: Chiabert, P., Bouras, A., Noël, F., Ríos, J. (eds.) PLM 2018. IAICT, vol. 540, pp. 46–55. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01614-2_5
Fernandez-Carames, T.M., Fraga-Lamas, P.: A review on human-centered IoT connected smart labels for the industry 4.0. IEEE Access 6, 25939–25957 (2018)
Jiao, Y., Zhang, S., Li, Y., Wang, Y., Yang, B.: Towards cloud augmented reality for construction application by BIM and SNS integration. Autom. Constr. 33, 37–47 (2013)
Karsch, K., Golparvar-Fard, M., Forsyth, D.: Constructaide: analysing and visualizing construction sites through photographs and building models. ACM Trans. Graph. (TOG) 33(6), 176 (2014)
Fusco, G., Coughlan, J.M.: Indoor localization using computer vision and visual-inertial odometry. In: Miesenberger, K., Kouroupetroglou, G. (eds.) ICCHP 2018. LNCS, vol. 10897, pp. 86–93. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94274-2_13
Knoth, L., Mittlbock, M., Vockner, B.: Smart 3D building infrastructures: linking GIS with other domains. ISPRS Ann. Photogrammetry Remote Sens. Spatial Inf. Sci. 4, 187 (2016)
Moloney, J.: Augmented reality visualisation of the built environment to support design decision making. In: Tenth International Conference on Information Visualisation (IV 2006), pp. 687–692, July 2006
Fraga-Lamas, P., Fernandez-Carames, T.M., Blanco-Novoa, O., Vilar-Montesinos, M.A.: A review on industrial augmented reality systems for the industry 4.0 shipyard. IEEE Access 6, 13358–13375 (2018)
Moon, S., Seo, J.: Integration of smart glass technology for information exchange at construction sites. In: ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction, vol. 32, p. 1 (2015)
Memarzadeh, M., Golparvar-Fard, M., Niebles, J.C.: Automated 2D detection of construction equipment and workers from site video streams using histograms of oriented gradients and colours. Autom. Constr. 32, 24–37 (2013)
Park, M.W., Koch, C., Brilakis, I.: Three-dimensional tracking of construction resources using an on-site camera system. J. Comput. Civil Eng. 26(4), 541–549 (2011)
Microsoft. 2017 Microsoft indoor localization competition (2017)
Marr, D., Hildreth, E.: Theory of edge detection. Proc. R. Soc. Lond. B 207(1167), 187–217 (1980)
Durrant-Whyte, H., Bailey, T.: Simultaneous localization and mapping: part i. IEEE Robot. Autom. Mag. 13(2), 99–110 (2006)
Fuentes-Pacheco, J., Ruiz-Ascencio, J., Rendon-Mancha, J.M.: Visual simultaneous localization and mapping: a survey. Artif. Intell. Rev. 43(1), 55–81 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Minneci, G., Schweigkofler, A., Marcher, C., Monizza, G.P., Tillo, T., Matt, D.T. (2019). Computer Vision Approach for Indoor Location Recognition Within an Augmented Reality Mobile Application. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2019. Lecture Notes in Computer Science(), vol 11792. Springer, Cham. https://doi.org/10.1007/978-3-030-30949-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-30949-7_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30948-0
Online ISBN: 978-3-030-30949-7
eBook Packages: Computer ScienceComputer Science (R0)