Pantœnna: Mouth Pose Estimation for AR/VR Headsets Using Low-Profile Antenna and Impedance Characteristic Sensing

要旨

Methods for faithfully capturing a user's holistic pose have immediate uses in AR/VR, ranging from multimodal input to expressive avatars. Although body-tracking has received the most attention, the mouth is also of particular importance, given that it is the channel for both speech and facial expression. In this work, we describe a new RF-based approach for capturing mouth pose using an antenna integrated into the underside of a VR/AR headset. Our approach side-steps privacy issues inherent in camera-based methods, while simultaneously supporting silent facial expressions that audio-based methods cannot. Further, compared to bio-sensing methods such as EMG and EIT, our method requires no contact with the wearer's body and can be fully self-contained in the headset, offering a high degree of physical robustness and user practicality. We detail our implementation along with results from two user studies, which show a mean 3D error of 2.6 mm for 11 mouth keypoints across worn sessions without re-calibration.

著者
Daehwa Kim
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Chris Harrison
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

https://doi.org/10.1145/3586183.3606805

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Sensing Sorcery: Novel Sensing Techniques and Systems

Venetian Room
6 件の発表
2023-11-01 01:00:00
2023-11-01 02:20:00