Impact of Parameter Disentanglement on Collaborative Alignment

Song T, Martin-Gomez A, Wang Q, Mehrfard A, Fotouhi J, Roth D, Eck U, Navab N (2022)


Publication Type: Conference contribution

Publication year: 2022

Publisher: Institute of Electrical and Electronics Engineers Inc.

Pages Range: 560-561

Conference Proceedings Title: Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022

Event location: Virtual, Online, NZL

ISBN: 9781665484022

DOI: 10.1109/VRW55335.2022.00131

Abstract

The interactive alignment of real and virtual content in AR is often non-trivial. Positional errors along the users view direction frequently lead to the misjudgment of the objects depth. This work takes advantage of alternative users' viewpoints in collaborative settings to mitigate these errors. Furthermore, we systematically restrict the parameters used to control the virtual contents pose and investigate the impact of sharing and disentangling such parameters. Results from this work show that alignment schemes that disentangle the control parameters improve overall alignment accuracy with a similar workload for the users and no significant increase in execution time.

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How to cite

APA:

Song, T., Martin-Gomez, A., Wang, Q., Mehrfard, A., Fotouhi, J., Roth, D.,... Navab, N. (2022). Impact of Parameter Disentanglement on Collaborative Alignment. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 560-561). Virtual, Online, NZL: Institute of Electrical and Electronics Engineers Inc..

MLA:

Song, Tianyu, et al. "Impact of Parameter Disentanglement on Collaborative Alignment." Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022, Virtual, Online, NZL Institute of Electrical and Electronics Engineers Inc., 2022. 560-561.

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