Recent advances in 3D scanning, reconstruction, and animation techniques have made it possible to rapidly create photorealistic avatars based on real people. While it is now possible to create personalized avatars automatically with consumer-level technology, their visual fidelity still falls far short of 3D avatars created with professional cameras and manual artist effort. To evaluate the importance of investing resources in the creation of high-quality personalized avatars, we conducted an experiment to investigate the effects of varying their visual texture fidelity, specifically focusing on identity recognition of specific individuals. We designed two virtual reality experimental scenarios: (1) selecting a specific avatar from a virtual lineup and (2) searching for an avatar in a virtual crowd. Our results showed that visual fidelity had a significant impact on participants' abilities to identify specific avatars from a lineup wearing a head-mounted display. We also investigated gender effects for both the participants and the confederates from which the avatars were created.
|Original language||English (US)|
|Title of host publication||International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, ICAT-EGVE 2017|
|Editors||Robert W. Lindeman, Gerd Bruder, Daisuke Iwai|
|Number of pages||4|
|State||Published - 2017|
|Event||27th International Conference on Artificial Reality and Telexistence, ICAT 2017 and the 22nd Eurographics Symposium on Virtual Environments, EGVE 2017 - Adelaide, Australia|
Duration: Nov 22 2017 → Nov 24 2017
|Name||International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, ICAT-EGVE 2017|
|Conference||27th International Conference on Artificial Reality and Telexistence, ICAT 2017 and the 22nd Eurographics Symposium on Virtual Environments, EGVE 2017|
|Period||11/22/17 → 11/24/17|
Bibliographical noteFunding Information:
The work depicted here is sponsored by the U.S. Army Research Laboratory (ARL) under contract number W911NF-14-D-0005 and the National Science Foundation (NSF) grant number CNS-1560426. Statements and opinions expressed and content included do not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
© 2017 The Author(s).
Copyright 2020 Elsevier B.V., All rights reserved.