Google AR & VR and University of Central Florida collaborated on a study to validate VALID, a virtual avatar library comprising 210 fully rigged avatars representing seven races. The study, which involved a global participant pool, revealed consistent recognition for some races and own-race bias effects. The team highlighted implications for virtual avatar applications and provided open access to the VALID library.
Google AI and University of Central Florida’s Virtual Avatar Library for Inclusion and Diversity (VALID)
Creating a Diverse Virtual Avatar Library
The research team collaborated to validate a virtual avatar library called VALID, consisting of 210 fully rigged avatars representing seven diverse races. The study involved a global participant pool to obtain validated labels and metadata for the perceived race and gender of each avatar. Results revealed consistent recognition of Asian, Black, and White avatars by participants of various races. However, avatars representing certain races showed more ambiguity, with differences in perception based on participant race.
Practical Implications
The study highlighted the impact of own-race bias on avatar perception and emphasized the importance of considering participants’ race in virtual avatar research to ensure accurate representation. The open-access VALID library offers diverse avatars suitable for various scenarios, with 65 facial blend shapes for dynamic expressions and compatibility with popular game engines like Unity and Unreal.
Value for Middle Managers
The VALID library provides practical solutions for middle managers seeking diverse and inclusive avatars for their applications. It challenges stereotypes, promotes inclusion, and offers valuable insights for developing and applying virtual avatars in various fields.
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