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Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation

Feng, Qi; Shum, Hubert P.H.; Morishima, Shigeo

Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation Thumbnail


Authors

Qi Feng

Shigeo Morishima



Abstract

Pre-captured immersive environments using omnidirectional cameras provide a wide range of virtual reality applications. Previous research has shown that manipulating the eye height in egocentric virtual environments can significantly affect distance perception and immersion. However, the influence of eye height in pre-captured real environments has received less attention due to the difficulty of altering the perspective after finishing the capture process. To explore this influence, we first propose a pilot study that captures real environments with multiple eye heights and asks participants to judge the egocentric distances and immersion. If a significant influence is confirmed, an effective image-based approach to adapt pre-captured real-world environments to the user’s eye height would be desirable. Motivated by the study, we propose a learning-based approach for synthesizing novel views for omnidirectional images with altered eye heights. This approach employs a multitask architecture that learns depth and semantic segmentation in two formats, and generates high-quality depth and semantic segmentation to facilitate the inpainting stage. With the improved omnidirectional-aware layered depth image, our approach synthesizes natural and realistic visuals for eye height adaptation. Quantitative and qualitative evaluation shows favorable results against state-of-the-art methods, and an extensive user study verifies improved perception and immersion for pre-captured real-world environments.

Citation

Feng, Q., Shum, H. P., & Morishima, S. (2023). Enhancing Perception and Immersion in Pre-Captured Environments through Learning-Based Eye Height Adaptation. In 2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). https://doi.org/10.1109/ISMAR59233.2023.00055

Presentation Conference Type Conference Paper (Published)
Conference Name ISMAR 23: International Symposium on Mixed and Augmented Reality
Start Date Oct 16, 2023
End Date Oct 20, 2023
Acceptance Date Aug 10, 2023
Online Publication Date Dec 4, 2023
Publication Date Dec 4, 2023
Deposit Date Aug 16, 2023
Publicly Available Date Dec 4, 2023
Publisher Institute of Electrical and Electronics Engineers
Series ISSN 1554-7868
Book Title 2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
ISBN 9798350328394
DOI https://doi.org/10.1109/ISMAR59233.2023.00055
Public URL https://durham-repository.worktribe.com/output/1718711

Files

Accepted Conference Paper (15.4 Mb)
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© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.





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