A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments

Duke Gledhill; Matthew Novak

doi:10.1109/MetroXRAINE58569.2023.10405684

A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we introduce a novel methodology for the optimization of photogrammetry data of physical objects for use in metaverse virtual environments. Our approach focuses on an artist-driven process to optimize mesh and textures derived from photogrammetry, ensuring authentic and accurate recreation of real-world objects for low-powered VR devices. By leveraging this methodology, we aim to enhance the user experience in virtual environments by providing realistic and immersive representations of physical objects while maintaining optimal performance on a wide range of devices. This paper details the development and implementation of our methodology, as well as its potential applications and benefits in the rapidly evolving metaverse landscape.

Original language	English
Title of host publication	2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering
Subtitle of host publication	IEEE MetroXRAINE 2023
Publisher	IEEE
Pages	40-45
Number of pages	6
ISBN (Electronic)	9798350300802, 9798350300796
ISBN (Print)	9798350300819
DOIs	https://doi.org/10.1109/MetroXRAINE58569.2023.10405684
Publication status	Published - 1 Feb 2024
Event	IEEE International Conference on Metrology for eXtended Reality Artificial Intelligence and Neural Engineering - Milan, Italy Duration: 25 Oct 2023 → 27 Oct 2023 https://www.metroxraine.org/

Conference

Conference	IEEE International Conference on Metrology for eXtended Reality Artificial Intelligence and Neural Engineering
Abbreviated title	IEEE MetroXRAINE 2023
Country/Territory	Italy
City	Milan
Period	25/10/23 → 27/10/23
Internet address	https://www.metroxraine.org/

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10.1109/MetroXRAINE58569.2023.10405684Licence: Unspecified

Cite this

Gledhill, D., & Novak, M. (2024). A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments. In 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering: IEEE MetroXRAINE 2023 (pp. 40-45). [10405684] IEEE. https://doi.org/10.1109/MetroXRAINE58569.2023.10405684

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title = "A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments",

abstract = "In this paper, we introduce a novel methodology for the optimization of photogrammetry data of physical objects for use in metaverse virtual environments. Our approach focuses on an artist-driven process to optimize mesh and textures derived from photogrammetry, ensuring authentic and accurate recreation of real-world objects for low-powered VR devices. By leveraging this methodology, we aim to enhance the user experience in virtual environments by providing realistic and immersive representations of physical objects while maintaining optimal performance on a wide range of devices. This paper details the development and implementation of our methodology, as well as its potential applications and benefits in the rapidly evolving metaverse landscape.",

keywords = "image processing, virtual reality, photogrammetry, optimization technique",

author = "Duke Gledhill and Matthew Novak",

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Gledhill, D & Novak, M 2024, A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments. in 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering: IEEE MetroXRAINE 2023., 10405684, IEEE, pp. 40-45, IEEE International Conference on Metrology for eXtended Reality Artificial Intelligence and Neural Engineering, Milan, Italy, 25/10/23. https://doi.org/10.1109/MetroXRAINE58569.2023.10405684

A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments. / Gledhill, Duke ; Novak, Matthew.

2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering: IEEE MetroXRAINE 2023. IEEE, 2024. p. 40-45 10405684.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments

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N2 - In this paper, we introduce a novel methodology for the optimization of photogrammetry data of physical objects for use in metaverse virtual environments. Our approach focuses on an artist-driven process to optimize mesh and textures derived from photogrammetry, ensuring authentic and accurate recreation of real-world objects for low-powered VR devices. By leveraging this methodology, we aim to enhance the user experience in virtual environments by providing realistic and immersive representations of physical objects while maintaining optimal performance on a wide range of devices. This paper details the development and implementation of our methodology, as well as its potential applications and benefits in the rapidly evolving metaverse landscape.

AB - In this paper, we introduce a novel methodology for the optimization of photogrammetry data of physical objects for use in metaverse virtual environments. Our approach focuses on an artist-driven process to optimize mesh and textures derived from photogrammetry, ensuring authentic and accurate recreation of real-world objects for low-powered VR devices. By leveraging this methodology, we aim to enhance the user experience in virtual environments by providing realistic and immersive representations of physical objects while maintaining optimal performance on a wide range of devices. This paper details the development and implementation of our methodology, as well as its potential applications and benefits in the rapidly evolving metaverse landscape.

KW - image processing

KW - virtual reality

KW - photogrammetry

KW - optimization technique

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BT - 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering

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T2 - IEEE International Conference on Metrology for eXtended Reality Artificial Intelligence and Neural Engineering

Y2 - 25 October 2023 through 27 October 2023

ER -

A Novel Methodology for the Optimization of Photogrammetry Data of Physical Objects for Use in Metaverse Virtual Environments

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