TY - GEN
T1 - GazeChat
T2 - 34th Annual ACM Symposium on User Interface Software and Technology, UIST 2021
AU - He, Zhenyi
AU - Wang, Keru
AU - Feng, Brandon Yushan
AU - Du, Ruofei
AU - Perlin, Ken
N1 - Publisher Copyright:
© 2021 Owner/Author.
PY - 2021/10/10
Y1 - 2021/10/10
N2 - Communication software such as Clubhouse and Zoom has evolved to be an integral part of many people's daily lives. However, due to network bandwidth constraints and concerns about privacy, cameras in video conferencing are often turned off by participants. This leads to a situation in which people can only see each others' profile images, which is essentially an audio-only experience. Even when switched on, video feeds do not provide accurate cues as to who is talking to whom. This paper introduces GazeChat, a remote communication system that visually represents users as gaze-aware 3D profile photos. This satisfies users' privacy needs while keeping online conversations engaging and efficient. GazeChat uses a single webcam to track whom any participant is looking at, then uses neural rendering to animate all participants' profile images so that participants appear to be looking at each other. We have conducted a remote user study (N=16) to evaluate GazeChat in three conditions: audio conferencing with profile photos, GazeChat, and video conferencing. Based on the results of our user study, we conclude that GazeChat maintains the feeling of presence while preserving more privacy and requiring lower bandwidth than video conferencing, provides a greater level of engagement than to audio conferencing, and helps people to better understand the structure of their conversation.
AB - Communication software such as Clubhouse and Zoom has evolved to be an integral part of many people's daily lives. However, due to network bandwidth constraints and concerns about privacy, cameras in video conferencing are often turned off by participants. This leads to a situation in which people can only see each others' profile images, which is essentially an audio-only experience. Even when switched on, video feeds do not provide accurate cues as to who is talking to whom. This paper introduces GazeChat, a remote communication system that visually represents users as gaze-aware 3D profile photos. This satisfies users' privacy needs while keeping online conversations engaging and efficient. GazeChat uses a single webcam to track whom any participant is looking at, then uses neural rendering to animate all participants' profile images so that participants appear to be looking at each other. We have conducted a remote user study (N=16) to evaluate GazeChat in three conditions: audio conferencing with profile photos, GazeChat, and video conferencing. Based on the results of our user study, we conclude that GazeChat maintains the feeling of presence while preserving more privacy and requiring lower bandwidth than video conferencing, provides a greater level of engagement than to audio conferencing, and helps people to better understand the structure of their conversation.
KW - eye contact
KW - gaze awareness
KW - gaze interaction
KW - video conferencing
KW - video-mediated communication
UR - http://www.scopus.com/inward/record.url?scp=85118202363&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85118202363&partnerID=8YFLogxK
U2 - 10.1145/3472749.3474785
DO - 10.1145/3472749.3474785
M3 - Conference contribution
AN - SCOPUS:85118202363
T3 - UIST 2021 - Proceedings of the 34th Annual ACM Symposium on User Interface Software and Technology
SP - 769
EP - 782
BT - UIST 2021 - Proceedings of the 34th Annual ACM Symposium on User Interface Software and Technology
PB - Association for Computing Machinery, Inc
Y2 - 10 October 2021 through 14 October 2021
ER -