Photogrammetric Race-Making in the MetaHuman Creator

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Chia, Aleena. 2025. Photogrammetric Race-Making in the MetaHuman Creator. In: Sian Mitchell; Colin Perry; Sean Redmond and Lienors Torre, eds. The Screens of Virtual Production: What is Real? Abingdon: Routledge, pp. 174-193. ISBN 9781032730721 [Book Section]

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Abstract or Description

While the dominant aspiration for human beauty on social media is smoothness and symmetry, the benchmark for quality in digital humans is texture and irregularity. Within the visual economy of hyperreal videogames, imperfection imparts character to artificial beings, enhancing their capacity to engage, influence, and entertain. Requiring more resources to model, visual character can now be blended from databases of diverse facial features, skin tones, and hair textures captured from photogrammetric scans of real humans. Predominantly white makers of digital human tools such as Epic Games’ MetaHuman Creator promote their ‘diverse series of presets’ as empowering equitable character creation. Scholars of post-race call out these practices as diversity surfing, which casts race as a cosmetic rather than political category, producing compliant digital humans who stand in for Black and creators of colour. Building on this scholarship, this chapter analyses how tools such as MetaHuman Creator abstract racial diversity as mathematical fact derived from databases of photogrammetric human scans. The MetaHuman Creator implements a data-based and asset-driven approach to race-making. As an imaging technology, MetaHuman marginalises minority representations, treating them as optional, fragmented, and peripheral to a default model of techno-physiological functioning. As a computational synthesis of race, MetaHuman dissolves racial concepts within the latent space of statistical compression. Beyond these post-racial logics, the MetaHuman Creator undermines the basis for diversity politics, by framing diversity as a priori to racial concepts and classifications.

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Book Section

Identification Number (DOI):

https://doi.org/10.4324/9781003463139-15