By CHRIS SWIATEK, ICVR
Edited for this publication by Jeffrey A. Okun, VES Abstracted from The VES Handbook of Virtual Production Edited by Susan Zwerman, VES and Jeffrey A. Okun, VES
By CHRIS SWIATEK, ICVR
Edited for this publication by Jeffrey A. Okun, VES Abstracted from The VES Handbook of Virtual Production Edited by Susan Zwerman, VES and Jeffrey A. Okun, VES
Introduction
The Virtual Art Department (VAD) production period concludes with final optimization, stage testing and delivery of the content to the stage before shooting.
This period begins with delivery of the VAD content to the stage, after which it is thoroughly tested in the target environment. Any remaining issues are identified, resolved, re-tested and approved before shooting begins.
The specifics of this process vary depending on the nature of the production and how closely the VAD and stage operations team are connected. On some productions these responsibilities are handled by the same vendor, while other times they may operate as distinctly separate teams. Regardless of team struc- ture, the delivery and testing period should be a collaborative process between the stage operations and VAD teams and requires efficient two-way exchange of communication and data.
Asset Delivery
Content is first delivered to the stage, then loaded onto the target hardware and tested before shooting begins. Game engine assets are managed using source control software, which stores files on a central server and enables collaboration between large teams without overwriting work.
Because the testing stage should be a collaboration between the VAD team and stage operations team, keeping the project hosted on source control is critical to ensuring a smooth two-way exchange of data. The stage team receives the content, tests it on the wall and makes initial tweaks to fix any obvious issues. The stage team can then push these changes back to the server so they are instantly received by the VAD team. Subsequent changes can then be made by the VAD team without fear of overwriting the initial changes made by the stage team. Without source control, any changes made by either team would have to be manually merged, introducing a higher likelihood of error and slowing down the testing process.
Delivery of content to the stage without the use of source control is only recommended in situations where the VAD team is not involved at all in testing or optimization and performs a strict linear handoff. This scenario is not recommended as it is always more efficient for the same team who originally created the content to also perform optimization and technical fixes.
Stage Testing
Once the content is delivered to the stage opera- tions team, it is tested on stage hardware in the final shooting environment. The content is benchmarked and stress-tested to ensure it hits the target frame rate. For an LED shoot, the visual quality of the content is analyzed on the wall and through a camera lens. Any performance issues or visual issues are recorded and documented so they can be fixed before the shoot. In the interest of efficiency, the stage operations team may immediately fix simple issues that come up during testing, while more in-depth issues are relayed back to the VAD team.
Optimizing for Target Hardware
By the time content is delivered to the stage, it should already be optimized well for the target hardware (see “Managing Asset Quality and Performance Needs for Virtual Production”). Even with careful planning and testing, unexpected performance issues sometimes appear during stage testing that were not obvious in the VAD test environment.
Many issues can be narrowed down quickly by using Unreal Engine’s optimization View Modes to identify problem areas or using Multi-user Editor on stage to turn scene objects on and off until the culprit object(s) is found. These techniques are helpful for revealing simple problems with straightforward fixes, like overlapping transparent textures, too many emissive light sources or too much foliage. If these techniques do not pinpoint the problem, scene profiling can be used to identify bottlenecks.
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