Identification with AR Face Filters and societal biases

This project aims to explore Augmented Reality (AR) user identification with AR virtual avatars from a human centered perspective.

Identification is a psychological phenomenon representing the merger of user and avatar which forms a new identity. Normally AR identification research is limited to the mechanics of a system and improving immersion. This project will instead focus on the unique psychological experiences AR identification produces. In AR when there is a user x avatar interaction the real and virtual worlds are co-present. The avatar is not a stand-in for the user in a virtual space as in fully immersive VR. Instead the user’s body is either augmented with virtual elements or a virtual avatar is placed in the same real world environment as the user. The avatar and user inhabit the same space at the same time and the user is asked to identify with the avatar while being fully aware of their own body.

This project aims to explore AR identification and dual-presence for systems that augment and replace users; as well as, how AR identification might affect users’ attitudes and behaviors. Past research has shown that identification with VR and video game avatars can do such things as; improve users’ cognitive abilities, change users’ self-perceptions, and reduce users’ societal biases . As AR avatar identification requires users to be aware of themselves and the avatar at the same time it’s possible these effects could manifest in drastically differently.

Thus, this project aims to improve our understanding of the psychological impacts of AR identification. Since, VR and video game identification have been found to have such varied significant effects on users, understanding AR identification could not only improve the technology but help researchers and developers promote multiple positive changes in society.

Etienne Peillard
Etienne Peillard
Associate Professor

My research interests include human perception issues in Virtual and Augmented Reality, spatial perception in virtual and augmented environments, and more generally, the effect of perceptual biases in mixed environments.