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Exploration of using face tracking to reduce GPU rendering on current and future auto-stereoscopic displays

Published: 28 July 2019 Publication History

Abstract

Future auto-stereoscopic displays offer us an amazing possibility of virtual reality without the need for head mounted displays. Since fundamentally though we only need to generate viewpoints for known observers, the classical approach to render all views at once is wasteful in terms of GPU resources and limits the scale of an auto-stereoscopic display. We present a technique that reduces GPU consumption when using an auto-stereoscopic displays by giving the display a context awareness of its observers. The technique was first applied to the Looking Glass device on the Unity3D platform. Rather than rendering 45 different views at the same time, for each observer, the framework only requires six views that are visible to both eyes based on the tracked eye positions. Given the current specifications of this device, the framework helps save 73% GPU consumption for Looking Glass if it was to render a 8K X 8K resolution scene, and the saved GPU consumption increases as the resolution increases. This technique can be applied to reduce future GPU requirements for auto-stereoscopic displays in the future.

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Reference

[1]
Anjul Patney, Marco Salvi, Joohwan Kim, Anton Kaplanyan, Chris Wyman, Nir Benty, David Luebke, and Aaron Lefohn. 2016. Towards foveated rendering for gaze-tracked virtual reality. ACM Transactions on Graphics (TOG) 35, 6 (2016), 179.

Cited By

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  • (2023)Perceptual Assessment of Image and Depth Quality of Dynamically Depth-Compressed Scene for Automultiscopic 3D DisplayIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314841929:6(3067-3080)Online publication date: 1-Jun-2023
  • (2022)How can the Additional Motion Parallax along the y and z-axis Affect Viewer’s 3D Perception?: A Generic Approach and Evaluation2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR55827.2022.00040(252-259)Online publication date: Oct-2022
  • (2021)METAL: Explorations into Sharing 3D Educational Content across Augmented Reality Headsets and Light Field Displays2021 7th International Conference of the Immersive Learning Research Network (iLRN)10.23919/iLRN52045.2021.9459419(1-6)Online publication date: 17-May-2021
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cover image ACM Conferences
SIGGRAPH '19: ACM SIGGRAPH 2019 Posters
July 2019
148 pages
ISBN:9781450363143
DOI:10.1145/3306214
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2019

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View all
  • (2023)Perceptual Assessment of Image and Depth Quality of Dynamically Depth-Compressed Scene for Automultiscopic 3D DisplayIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314841929:6(3067-3080)Online publication date: 1-Jun-2023
  • (2022)How can the Additional Motion Parallax along the y and z-axis Affect Viewer’s 3D Perception?: A Generic Approach and Evaluation2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)10.1109/ISMAR55827.2022.00040(252-259)Online publication date: Oct-2022
  • (2021)METAL: Explorations into Sharing 3D Educational Content across Augmented Reality Headsets and Light Field Displays2021 7th International Conference of the Immersive Learning Research Network (iLRN)10.23919/iLRN52045.2021.9459419(1-6)Online publication date: 17-May-2021
  • (2021)Knowing Your Student: Targeted Teaching Decision Support Through Asymmetric Mixed Reality Collaborative LearningIEEE Access10.1109/ACCESS.2021.31345899(164742-164751)Online publication date: 2021
  • (2021)3D Displays: Their Evolution, Inherent Challenges and Future PerspectivesProceedings of the Future Technologies Conference (FTC) 2021, Volume 310.1007/978-3-030-89912-7_31(397-415)Online publication date: 25-Oct-2021
  • (2020)An Adaptive Low-cost Approach to Display Different Scenes to Multi-users for the Light Field DisplayProceedings of the 26th ACM Symposium on Virtual Reality Software and Technology10.1145/3385956.3422127(1-3)Online publication date: 1-Nov-2020
  • (2020)ARLS: An asymmetrical remote learning system for sharing anatomy between an HMD and a light field displayProceedings of the 26th ACM Symposium on Virtual Reality Software and Technology10.1145/3385956.3422095(1-2)Online publication date: 1-Nov-2020

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