Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production

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Publisher: SMPTE
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Motion Imaging Jour.
Volume: 134, No. 6, pp. 50–58
Abstract: The ability to capture a volumetric representation of performers in a production environment would enable a multitude of novel on-set and post-production workflows. Current methods are impractical due to their reliance on large numbers of cameras and consistent lighting conditions. We propose a framework for creating 2.5D assets from a single monocular video, allowing digitized performers to be viewed from a range of angles with the appearance of depth. An application processes the video offline, using depth and segmentation AI models to create a packaged 2.5D asset. This is then loaded into Disguise Designer for pre-visualisation of the performers within the virtual stage. Analysis of state-of-the-art depth inference models, using videos captured to represent the challenges of production environments, shows that it is possible to obtain coherent video depth maps in these conditions. However, metric models do not always accurately identify absolute depth values, and it is necessary to use models tailored specifically for video to ensure temporal consistency in the results. This work aims to serve as a foundation for more comprehensive 3D volumetric capture of performers in real-world production environments.
Publication Date: 2025-10-01
DOI: 10.5594/JMI.2025/FOOS6445
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/JMI.2025/FOOS6445
Author(s): Chris Nash
Nathan Butt
Andrea Loriedo
Robin Spooner
Taegyun Ha
Philip Coulam-Jones
James Bentley
Aljosa Smolic
Keyword(s): Volumetric Capture, Depth Estimation, Computer Vision, Virtual Production
Copyright: © 2025 SMPTE

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Chris Nash, Nathan Butt, Andrea Loriedo, Robin Spooner, Taegyun Ha, Philip Coulam-Jones, James Bentley, and Aljosa Smolic; Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production, MIJ 2025, Volume 134, Number 6 (pp. 50 to 58); SMPTE, 2025. Available at https://doi.org/10.5594/JMI.2025/FOOS6445

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Chris Nash, Nathan Butt, Andrea Loriedo, Robin Spooner, Taegyun Ha, Philip Coulam-Jones, James Bentley, and Aljosa Smolic; Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production, MIJ 2025, Volume 134, Number 6 (pp. 50 to 58); SMPTE, 2025. Available at https://doi.org/10.5594/JMI.2025/FOOS6445

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<span class="citation">Chris Nash, Nathan Butt, Andrea Loriedo, Robin Spooner, Taegyun Ha, Philip Coulam-Jones, James Bentley, and Aljosa Smolic; <cite>Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production</cite>, MIJ 2025, Volume 134, Number 6 (pp. 50 to 58); SMPTE, 2025. Available at <a href="https://doi.org/10.5594/JMI.2025/FOOS6445" target="_blank" rel="noopener">https://doi.org/10.5594/JMI.2025/FOOS6445</a></span>

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Chris Nash, Nathan Butt, Andrea Loriedo, Robin Spooner, Taegyun Ha, Philip Coulam-Jones, James Bentley, and Aljosa Smolic; Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production, MIJ 2025, Volume 134, Number 6 (pp. 50 to 58); SMPTE, 2025
doi: 10.5594/JMI.2025/FOOS6445
url: https://doi.org/10.5594/JMI.2025/FOOS6445

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Chris Nash, Nathan Butt, Andrea Loriedo, Robin Spooner, Taegyun Ha, Philip Coulam-Jones, James Bentley, and Aljosa Smolic; <cite id="bib-10-5594-jmi-2025-foos6445">Integration of Depth and Volumetric Capture Workflows for 2.5D Virtual Production</cite>, MIJ 2025, Volume 134, Number 6 (pp. 50 to 58); SMPTE, 2025
<span class="doi">10.5594/JMI.2025/FOOS6445</span>
</li>