Abstract
Computationally expensive rendering of virtual 3D objects in mixed reality applications of lightweight AR glasses can be performed by a remotely connected external server. However, nonnegligible 6DOF pose error caused by the remote rendering latency results in 3D visual inconsistency which can be hardly removed by 2D image correction using IMU. In this paper, we propose a novel 6DOF pose prediction algorithm based on learnable combination of consistent motion model and deep prediction. We formulate the combination of both as controlled residual learning and model ensemble. We build a dataset and demonstrate that our algorithm provides accurate prediction under 200ms.
Original language | English |
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Title of host publication | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781665441544 |
DOIs | |
Publication status | Published - 2022 |
Event | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 - Virtual, Online, United States Duration: 2022 Jan 7 → 2022 Jan 9 |
Publication series
Name | Digest of Technical Papers - IEEE International Conference on Consumer Electronics |
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Volume | 2022-January |
ISSN (Print) | 0747-668X |
Conference
Conference | 2022 IEEE International Conference on Consumer Electronics, ICCE 2022 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 22/1/7 → 22/1/9 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Keywords
- 6-DOF pose prediction
- AR glasses
- augmented reality
- deep learning
- mixed reality
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering