Name
Unreal Savings: Budget Previs/Techvis for Student Films
Date & Time
Thursday, October 27, 2022, 1:00 PM - 1:30 PM
Frank Deese
Description
Previs and Techvis are terms still largely associated with big budget motion pictures and tentpole streaming series. For filmmakers still in school or working with limited resources, the terms are more aspirational than practical to their present production endeavors. Yet some budding film directors, producers, and cinematographers on opposite sides of the globe have already recreated filming locations in Unreal to technically and accurately plan lighting, camera placement and movement, as well as the arrangement of actors on set before filming even begins, saving valuable hours on shooting days, while using only the most rudimentary Previs video and storyboard stills.

This presentation will examine how several young filmmakers took detailed measurements and photographs of their production locations – one of them in southern China – inputted all the location data into Unreal, populated their virtual sets with assets to recreate furniture and other elements of production design, then used the virtual sets in Unreal as if they were actually setting up for production on location. All this detailed planning was done in the comfort of their own homes and saved thousands of dollars in production hours on actual shooting days.

This Techvis and rudimentary Previs process is something that all film students and low budget film producers could employ at very little cost. The steps of the process are easily replicable and should become basic to film instruction. Being well practiced in using Unreal Engine will also be a valuable lead-in for more complex work in professional Previs, Techvis, and Virtual Production.
Location Name
Salon 1
Take-Aways from this Presentation
The goal of this session is to create a better appreciation for what is possible with Unreal Engine on a small scale, how students and low-budget filmmakers can begin immediately implementing the described technical steps others have discovered on their own, and how institutions and industry may benefit from greater production efficiency and the increasing demand for this kind of process.