Walton, DR, Kavakli, K, Dos Anjos, RK et al. (6 more authors) (2022) Metameric Varifocal Holograms. In: 2022 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). 2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR), 12-16 Mar 2022, Online. IEEE , pp. 746-755. ISBN 978-1-6654-9618-6
Abstract
Computer-Generated Holography (CGH) offers the potential for genuine, high-quality three-dimensional visuals. However, fulfilling this potential remains a practical challenge due to computational complexity and visual quality issues. We propose a new CGH method that exploits gaze-contingency and perceptual graphics to accelerate the development of practical holographic display systems. Firstly, our method infers the user’s focal depth and generates images only at their focus plane without using any moving parts. Second, the images displayed are metamers; in the user’s peripheral vision, they need only be statistically correct and blend with the fovea seamlessly. Unlike previous methods, our method prioritises and improves foveal visual quality without causing perceptually visible distortions at the periphery. To enable our method, we introduce a novel metameric loss function that robustly compares the statistics of two given images for a known gaze location. In parallel, we implement a model representing the relation between holograms and their image reconstructions. We couple our differentiable loss function and model to metameric varifocal holograms using a stochastic gradient descent solver. We evaluate our method with an actual proof-of-concept holographic display, and we show that our CGH method leads to practical and perceptually three-dimensional image reconstructions.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Computer-Generated Holography , Foveated Rendering , Metamerisation , Varifocal Near-Eye Displays , Virtual Reality , Augmented Reality |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Jun 2022 18:05 |
Last Modified: | 08 Apr 2025 15:11 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/vr51125.2022.00096 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187760 |