Back to Search Start Over

FaceOri: Tracking Head Position and Orientation Using Ultrasonic Ranging on Earphones

Authors :
Wang, Yuntao
Ding, Jiexin
Chatterjee, Ishan
Parizi, Farshid Salemi
Zhuang, Yuzhou
Yan, Yukang
Patel, Shwetak
Shi, Yuanchun
Publication Year :
2022

Abstract

Face orientation can often indicate users' intended interaction target. In this paper, we propose FaceOri, a novel face tracking technique based on acoustic ranging using earphones. FaceOri can leverage the speaker on a commodity device to emit an ultrasonic chirp, which is picked up by the set of microphones on the user's earphone, and then processed to calculate the distance from each microphone to the device. These measurements are used to derive the user's face orientation and distance with respect to the device. We conduct a ground truth comparison and user study to evaluate FaceOri's performance. The results show that the system can determine whether the user orients to the device at a 93.5% accuracy within a 1.5 meters range. Furthermore, FaceOri can continuously track the user's head orientation with a median absolute error of 10.9 mm in the distance, 3.7 degrees in yaw, and 5.8 degrees in pitch. FaceOri can allow for convenient hands-free control of devices and produce more intelligent context-aware interaction.<br />Comment: CHI Conference on Human Factors in Computing Systems (CHI'22), 12 pages

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2203.10553
Document Type :
Working Paper
Full Text :
https://doi.org/10.1145/3491102.3517698