TY - GEN
T1 - Face Off
T2 - 11th International Conference on Virtual Reality, ICVR 2025
AU - Sangeeth Chandran, J. K.
AU - Salvador, Marisa Llorens
AU - Ennis, Cathy
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Social virtual reality (VR) applications have become more ubiquitous in recent years; central to this is the communication pipeline, how users perceive virtual human facial expressions, and how they control them in real time, especially when using VR devices without face-tracking. We investigated both aspects in a set of experiments. Firstly, we compared the perception of virtual human emotions on a traditional 2D screen and in VR. In a second experiment, we used a validated set of stimuli to compare three different control methods for manipulating an avatar's facial expressions in VR. These control methods utilize non-tracking control techniques, which do not rely on real-time face tracking but rely on alternative inputs via the VR controller. Our analysis shows that in VR, the effectiveness ratings for happy, sad, and surprise were significantly higher, and disgust was significantly more recognizable, compared to the screen. These findings contribute to our understanding of virtual human based emotional communication in VR by demonstrating that the perception of facial expression varies between screen and VR. Additionally, we identify raycast selection (point and click) as the most accurate control method, whereas thumbstick labeled (using a controller thumbstick with UI labels for guidance) was the fastest and most preferred method by participants.
AB - Social virtual reality (VR) applications have become more ubiquitous in recent years; central to this is the communication pipeline, how users perceive virtual human facial expressions, and how they control them in real time, especially when using VR devices without face-tracking. We investigated both aspects in a set of experiments. Firstly, we compared the perception of virtual human emotions on a traditional 2D screen and in VR. In a second experiment, we used a validated set of stimuli to compare three different control methods for manipulating an avatar's facial expressions in VR. These control methods utilize non-tracking control techniques, which do not rely on real-time face tracking but rely on alternative inputs via the VR controller. Our analysis shows that in VR, the effectiveness ratings for happy, sad, and surprise were significantly higher, and disgust was significantly more recognizable, compared to the screen. These findings contribute to our understanding of virtual human based emotional communication in VR by demonstrating that the perception of facial expression varies between screen and VR. Additionally, we identify raycast selection (point and click) as the most accurate control method, whereas thumbstick labeled (using a controller thumbstick with UI labels for guidance) was the fastest and most preferred method by participants.
KW - avatar
KW - control method
KW - emotion perception
KW - facial expression
KW - virtual reality
KW - VR
UR - https://www.scopus.com/pages/publications/105019050352
U2 - 10.1109/ICVR66534.2025.11172599
DO - 10.1109/ICVR66534.2025.11172599
M3 - Conference contribution
AN - SCOPUS:105019050352
T3 - 2025 11th International Conference on Virtual Reality, ICVR 2025
SP - 126
EP - 134
BT - 2025 11th International Conference on Virtual Reality, ICVR 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 9 July 2025 through 11 July 2025
ER -