Using Facial Animation to Increase the Enfacement Illusion and Avatar Self-Identification.


Journal

IEEE transactions on visualization and computer graphics
ISSN: 1941-0506
Titre abrégé: IEEE Trans Vis Comput Graph
Pays: United States
ID NLM: 9891704

Informations de publication

Date de publication:
05 2020
Historique:
pubmed: 20 2 2020
medline: 2 4 2021
entrez: 20 2 2020
Statut: ppublish

Résumé

Through avatar embodiment in Virtual Reality (VR) we can achieve the illusion that an avatar is substituting our body: the avatar moves as we move and we see it from a first person perspective. However, self-identification, the process of identifying a representation as being oneself, poses new challenges because a key determinant is that we see and have agency in our own face. Providing control over the face is hard with current HMD technologies because face tracking is either cumbersome or error prone. However, limited animation is easily achieved based on speaking. We investigate the level of avatar enfacement, that is believing that a picture of a face is one's own face, with three levels of facial animation: (i) one in which the facial expressions of the avatars are static, (ii) one in which we implement lip-sync motion and (iii) one in which the avatar presents lip-sync plus additional facial animations, with blinks, designed by a professional animator. We measure self-identification using a face morphing tool that morphs from the face of the participant to the face of a gender matched avatar. We find that self-identification on avatars can be increased through pre-baked animations even when these are not photorealistic nor look like the participant.

Identifiants

pubmed: 32070973
doi: 10.1109/TVCG.2020.2973075
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2023-2029

Auteurs

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Classifications MeSH