Evaluation of Marker-Based AR-Tracking with Vuforia in the Context of Rail Vehicle Maintenance
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-28076-4_7
Reference8 articles.
1. Kovacs, K., Ansari, F., Geisert, C., Uhlmann, E., Glawar, R., Sihn, W.: A process model for enhancing digital assistance in knowledge-based maintenance. In: Beyerer, J., Kühnert, C., Niggemann, O. (eds.) Machine Learning for Cyber Physical Systems. TIA, vol 9, pp. 87–96, Springer, Berlin, Heidelberg (2019). https://doi.org/10.1007/978-3-662-58485-9_10
2. Müller, R., Vette-Steinkamp, M., Hörauf, L., Speicher, C., Bashir, A.: Worker centered cognitive assistance for dynamically created repairing jobs in rework area. In: 51st CIRP Conference on Manufacturing Systems (2018)
3. Meily, S.O., Putra, I.K.G.D., Buana, P.W.: Augmented reality using real-object tracking development. Jurnal Sistem Informasi 17(1), 20–29 (2021)
4. Union Internationale des Chemins de fer (UIC), UIC 571-1-5ed. Standard wagons - Ordinary two-axle wagons - Characteristics (2004)
5. Rieder, J.S.I., van Tol, D.H., Aschenbrenner, D.: Effective close-range accuracy comparison of Microsoft HoloLens Generation one and two using Vuforia ImageTargets. In: 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) (2021)
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